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{"poster":"Liliths","date":"2017-01-28T01:31:40.357+0000","title":"+1 Por las SKins PoolParty de Freljord !","subforum":"Charlas Generales","up_votes":43,"down_votes":6,"body":"http://las.leagueoflegends.com/sites/default/files/styles/scale_xlarge/public/upload/article.gameplay.1.full_.jpg?itok=c-lLYB7H\r\nRiot\r\n\r\nRiot, nos inspiraste :u.\r\nUno no sabe lo que quiere hasta que se lo muestran, y por dios... Mira esa Lissandra! (Soy muy fan de lissandra como campeona)\r\nEsa Ashe, esa Sejuani!","replies":[{"poster":"ØffTopic","date":"2017-01-28T02:30:29.111+0000","up_votes":3,"down_votes":6,"body":"Ya dijeron que no van a ser skins \n\nSaludos {{sticker:slayer-jinx-catface}}","replies":[{"poster":"Liliths","date":"2017-01-28T03:05:40.613+0000","up_votes":13,"down_votes":1,"body":"Tambien dijieron que ni iba a habe Modo Practica :u\nSaludos {{sticker:slayer-jinx-wink}}","replies":[{"poster":"Mr Society","date":"2017-01-28T14:39:31.048+0000","up_votes":2,"down_votes":0,"body":"te mereces un buen trago de cloralex >:v","replies":[]},{"poster":"ØffTopic","date":"2017-01-28T03:06:44.092+0000","up_votes":3,"down_votes":2,"body":"Me has dejado sin palabras toma tu {{item:2009}} te lo ganaste {{sticker:slayer-jinx-wink}}","replies":[{"poster":"Liliths","date":"2017-01-28T09:04:56.954+0000","up_votes":3,"down_votes":1,"body":"{{champion:201}} Esto ira para los Porrrrrros","replies":[]}]}]}]},{"poster":"Phyxerian","date":"2017-01-28T04:50:33.121+0000","up_votes":10,"down_votes":0,"body":"**PERO A ESA LISSANDRA YO LE CALIENTO TODO EL FRÉLJORD PAPÁ**","replies":[{"poster":"ImNw","date":"2017-01-28T14:28:44.539+0000","up_votes":1,"down_votes":0,"body":"Teoricamente no tiene piernas pero bueno todo es aceptable ( ͡° ͜ʖ ͡°)\nA lo sumo que le claven un pareo","replies":[]}]},{"poster":"LemønPykë","date":"2017-01-28T09:11:15.948+0000","up_votes":2,"down_votes":0,"body":"Anivia poolparty? ya notas lo loco que suena eso?","replies":[{"poster":"Liliths","date":"2017-01-28T09:18:25.897+0000","up_votes":6,"down_votes":0,"body":"390 RP, Le agrega un vaso con hielo en la Ala derecha :u {{champion:34}}","replies":[{"poster":"Nuke","date":"2017-01-28T20:36:39.194+0000","up_votes":1,"down_votes":0,"body":"http://st.elohell.net/public/chill/460b54c8f0e1f5a0f0a5ab9973ac36af.jpg","replies":[]}]}]},{"poster":"Mazer Rakham","date":"2017-01-28T01:48:20.333+0000","up_votes":7,"down_votes":1,"body":"Sólo te hago una corrección, es \"take\", no \"taky\". Por lo demás, si, quiero esas skins ♥.\n\nPd: Ese Olaf mirando desde el fondo como esperando el momento justo para gankearlas a todas juntas xD y el cangrejo con cara de \"qué miras?\"","replies":[{"poster":"Liliths","date":"2017-01-28T03:05:12.171+0000","up_votes":2,"down_votes":1,"body":"A veces escribo muy rapido y se me van las letras :v","replies":[{"poster":"Mazer Rakham","date":"2017-01-28T16:23:41.602+0000","up_votes":1,"down_votes":0,"body":"A todos nos pasa xD","replies":[]}]}]},{"poster":"faster51","date":"2017-01-28T01:41:53.986+0000","up_votes":6,"down_votes":1,"body":"necesito a esas chiquitas ( ͡° ͜ʖ ͡°)","replies":[{"poster":"Liliths","date":"2017-01-28T01:43:24.038+0000","up_votes":4,"down_votes":0,"body":"( ͡° ͜ʖ ͡°) +1","replies":[{"poster":"faster51","date":"2017-01-28T02:28:07.677+0000","up_votes":4,"down_votes":1,"body":"( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( ͡° ͜ʖ ͡°)( 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loquisho","replies":[]}]}]}]}]},{"poster":"Nuke","date":"2017-01-28T04:22:20.352+0000","up_votes":3,"down_votes":0,"body":"¡LOL! Crei que era Soraka, pues cuando veo piel azul acercandose a morado, es lo primero que pienso. ¿No crees que parece Soraka?","replies":[{"poster":"Liliths","date":"2017-01-28T09:06:51.510+0000","up_votes":2,"down_votes":1,"body":"Un buen conocedor sabe que {{champion:127}} es ciega{{champion:64}} , porque de niña la atacó un Ursino {{champion:106}} \n{{sticker:slayer-jinx-wink}}","replies":[{"poster":"Nuke","date":"2017-01-28T20:34:58.214+0000","up_votes":1,"down_votes":0,"body":"¿Ursino?\n\nhttps://www.google.com.ar/search?q=Ursino&espv=2&biw=1920&bih=974&source=lnms&tbm=isch&sa=X&ved=0ahUKEwig78v51-XRAhUKipAKHf1nCJ0Q_AUIBigB\n\nSe ve que tenia una maldicion y le crecieron patas.","replies":[]}]}]},{"poster":"NahuelG","date":"2017-01-28T04:08:19.536+0000","up_votes":3,"down_votes":0,"body":"ESA ASHE PAPA AHRE Xd es q es mi main{{champion:22}}","replies":[]},{"poster":"Hell Darking","date":"2017-01-28T03:07:21.685+0000","up_votes":3,"down_votes":0,"body":"pero mira esa anivia papu","replies":[]},{"poster":"TSW Rorschach","date":"2017-01-28T16:54:57.658+0000","up_votes":2,"down_votes":0,"body":"Yo me pido a esa Anivia tirando flotadores con la Q :'v","replies":[]},{"poster":"DameWeed","date":"2017-01-28T13:54:50.779+0000","up_votes":2,"down_votes":0,"body":"Me imaginé a Braum en una sunga roja. Esa yo me la compraría (?","replies":[]},{"poster":"IIIIIIIIIIIIIIII","date":"2017-01-28T08:03:29.005+0000","up_votes":2,"down_votes":0,"body":"Mira esa Lissandra papá!","replies":[]},{"poster":"faster51","date":"2017-01-28T03:41:22.553+0000","up_votes":2,"down_votes":0,"body":"a Anivia te la pasas por las [E de xerath multiplicada por 2]","replies":[]},{"poster":"TSM Zaca","date":"2017-01-29T03:58:57.610+0000","up_votes":1,"down_votes":0,"body":"que anivia sea una gaviota jajaj","replies":[]},{"poster":"Ema UwU","date":"2017-01-29T01:34:02.210+0000","up_votes":1,"down_votes":0,"body":"no pos a lolhentai punto net {{summoner:6}}","replies":[]},{"poster":"Yazuò","date":"2017-01-28T21:49:24.264+0000","up_votes":1,"down_votes":0,"body":"{{champion:23}} esta feliz con esto.","replies":[]},{"poster":"rockstar654321","date":"2017-01-28T21:03:16.740+0000","up_votes":1,"down_votes":0,"body":"miren a esa olaf papu xD {{sticker:slayer-pantheon-popcorn}}","replies":[]},{"poster":"derricoagustin","date":"2017-01-28T19:37:52.249+0000","up_votes":1,"down_votes":0,"body":"ojala que agan eso {{summoner:30}}","replies":[]},{"poster":"mathi8","date":"2017-01-28T19:06:10.360+0000","up_votes":1,"down_votes":0,"body":"No.","replies":[]},{"poster":"Elyasviel","date":"2017-01-28T18:55:08.768+0000","up_votes":1,"down_votes":0,"body":"Mira a esa anivia papu ( ͡° ͜ʖ ͡°)","replies":[]},{"poster":"MrDuks","date":"2017-01-28T18:26:22.887+0000","up_votes":1,"down_votes":0,"body":"Y todos se olvidan del bueno de olaf {{sticker:zombie-nunu-bummed}}","replies":[{"poster":"Liliths","date":"2017-01-28T18:29:17.835+0000","up_votes":1,"down_votes":0,"body":"Olaf noes Waifu de nadie :u","replies":[]}]},{"poster":"SphinxZeld","date":"2017-01-28T17:53:28.906+0000","up_votes":1,"down_votes":0,"body":"https://www.youtube.com/watch?v=aEKXGvhWYNg","replies":[]},{"poster":"Chukj","date":"2017-01-28T16:30:27.525+0000","up_votes":1,"down_votes":0,"body":"El que quiera regalar, aca estoy para recibir el regalo (? se ven muy buenas","replies":[]}]} |
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{"poster":"BodoxLP","date":"2015-10-24T22:35:32.824+0000","title":"Nicht mehr ins game kommen.","subforum":"Melde einen Bug","up_votes":2,"down_votes":0,"body":"Ich habe ein problem und zwar hab ich eine runde lol mit meinen freund gespielt da war alles gut,danach bin ich nochmal in ein game gegangen und bin in die lobby gekommen alles ging ich konnte meinen champ auswählen aber ich konnte nicht in den ladescreen rein ich denke das ist ein bug. Ich habe mein lol deinstalliert und wieder installiert aber es geht immer noch nicht falls ihr wisst woran das liegt bitte melden skymaster@t-online.de","replies":[{"poster":"LicensedCrime","date":"2015-10-24T23:24:04.863+0000","up_votes":1,"down_votes":0,"body":"Ich komm auch nicht ins game und bekomme ne Netzwerkwarnung. Die Verbindung wurde einfach unterbrochen! Firewall ist richtig eingestellt!","replies":[]},{"poster":"Gin","date":"2015-10-24T23:14:55.100+0000","up_votes":1,"down_votes":0,"body":"Wenn du nicht in den Loading Screen reinkommst hilft meistens Client neustarten.","replies":[]},{"poster":"ETS cYa","date":"2015-10-24T22:46:03.504+0000","up_votes":1,"down_votes":0,"body":"den admin lol launcher im riotgames ordner benutzen","replies":[]}]} |
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{"poster":"tLc Fatcat","date":"2015-02-26T17:26:42.830+0000","title":"LoL-Clan SnitzelNuggetz sucht Spieler ! (+15 - 17)","subforum":"Clans & Teams","up_votes":1,"down_votes":0,"body":"Hey Leute,\r\n\r\nWir suchen Spieler für den League of Legends Clan SnitzelNuggetz. ;)\r\n\r\nWir sind:\r\n- Fatdog (Silber 5, spielt seit Season 3) und Fatcat (Bronze 1, spielt seit Season 4),\r\n- beide 16 Jahre alt,\r\n- Freundlich ;)\r\n\r\nIhr solltet:\r\n- zwischen 15 und 17 Jahre alt sein,\r\n- Teamspeak ist nicht erforderlich (Wir haben aber einen Server),\r\n- Gewinnen wollen,\r\n- seit mindestens Season 4 LoL spielen,\r\n- ebenfalls Freundlich sein, ;)\r\n\r\nWenn Ihr Lust habt einfach mal einen von uns in LoL anschreiben. :) \r\n\r\nLiebe Grüße,\r\n\r\n\r\nIngame: tLc Fatcat, tLc Fatdog","replies":[]} |
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Both these models have their own advantages as well as challenges and it is valuable that these co-exist in the field. We highlight key differences between these models as follows.\n- Theoretical backbone: CGF is heavily entangled with Neural Ordinary Differential Equations \u2014 requires solving initial value problem and has continuous time property. GNF, on the other hand, is purely based on change of variable formula. They shall be treated differently.\n- Application: GNF and CGF can both be used for generating static graph structured data. In addition, since CGF is capable of modeling continuous time dynamics of graph-structured variables, the CGF can also be potentially applied to graph data having regular and irregular time dynamics.\n\n*Discussion about GraphNVP\nWe agree that GraphNVP is a relevant related work in this field. However, we believe GraphNVP is based on normalizing flow based models which are different from CGF which is based on neural ordinary differential equations (ODEs). We have cited and discussed this work in the updated paper.\n\n*Comparison with concurrent work\nWe would like to clarify that GNF is a concurrent work developed in parallel and not a previous work. We only use their numbers on graph generation experiments for better reference and don\u2019t use it as a standard baseline. We are happy to discuss the differences between the models (in the following part), but we are not claiming full contributions over GNF. \n\n\n*Choices of f-hat and g: \nWe apologize for the confusion. f_hat (x_i,x_j) is given by f_u (x_i) + f_b(x_i,x_j) for all j in the set of neighbors of node in the graph. To clarify the implementation details, we chose two types of functions for f_u and f_b as convolutional networks for puzzle graph generation and linear neural networks for scene graph based layout generation and graph generation. The function g is the mean of all the outputs f_hat used to aggregate these message functions. \n\n*CGF for continuous time dynamics for graphs (reasons): \nThank you for the comment.\n- Continuous normalizing flow is the state-of-the-art flow-based model which yield a powerful tool for modeling graph distributions\n- The freedom on incorporating any function types as message functions. This allows the model to be general and makes it applicable to various types of graph neural networks in graph generation setting.\n- There is potential to use our model for continuous time graph data, especially on irregular timestamps. It\u2019s a promising direction for future work. \n\n*Discrete vs. continuous experiments:\n- First of all, the functions in continuous dynamics cannot be used in discrete cases, since the discrete flow has limitation on using specific function types (reversible functions with easy to compute Jacobian determinant)\n- Secondly, for the standard discrete normalizing flow and continuous dynamic based flow, this experiments are already presented in FFJORD paper which compares the capacity of popular discrete models and the proposed continuous dynamics based flow. \n"}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. 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Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). 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If replying to a specific person make sure to add the group they are a member of so that they are able to see your response"}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+|ICLR.cc/2020/Conference/Paper1101/Authors|ICLR.cc/2020/Conference/Paper1101/Area_Chair[0-9]+|ICLR.cc/2020/Conference/Program_Chairs"}}, "readers": ["everyone"], "tcdate": 1569504161241, "tmdate": 1576860536967, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment"}}}, {"id": "H1xDXdR7sS", "original": null, "number": 2, "cdate": 1573279775261, "ddate": null, "tcdate": 1573279775261, "tmdate": 1573329261397, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgReQ9aKB", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment", "content": {"title": "Response to Reviewer #1", "comment": "We would like to thank the reviewer for the thorough and valuable feedback for the manuscript. We updated the manuscript and the changes are marked by red color. We first list our contributions and then provide clarifications on the specific concerns listed in the reviewer\u2019s comments.\n\n\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014-\u2014\u2014\u2014-Our contributions\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\nWe propose Continuous Graph Flow (CGF) - a continuous time flow-based model for graph structured data. In particular,\n- CGF integrates neural ODE based model and message passing (in graph neural networks) to model distributions of complex graph-structured data. Our work is among the first ones in this direction.\n- CGF learns flexible representations to handle variable data dimensions. In addition, given that CGF is based on NeuralODE, it inherits various advantages of NeuralODE such as reversibility, unconstrained functions in model design and exact likelihood computation. \n\n\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014-\u2014\u2014--Response to questions\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014----\n\n*Discussion about CGF and GNF. \n\nWe would like to clarify that GNF and CGF are fundamentally two different flow based models for graph-structured data. Both these models have their own advantages as well as challenges and it is valuable that these co-exist in the field.\n- Theoretical backbone: CGF is heavily entangled with Neural Ordinary Differential Equations \u2014 requires solving initial value problem and has continuous time property. GNF, on the other hand, is purely based on change of variable formula. They shall be treated differently.\n- Further improvements in models: Given that CGF and GNF rely on two different theoretical backbones, advances in the fields of Normalizing flows and Neural ODEs can potentially result in more powerful graph flow models on two independent directions. We appreciate the reviewer for pointing out the recent work on Flow++ and Neural spline flows which study improved techniques to enforce invertibility in functions. On the other hand, CGF has flexible functions in the model design. Moreover, the recent work on ordinary differential equations, such as Augmented Neural ODE [1] and Neural Jump SDE [2] can be applied to CGF or follow-up works for improving their performance, but potentially are less useful for normalizing flow-based models.\n\n*Comparison with concurrent work\nWe would like to clarify that GNF is a concurrent work developed in parallel and not a previous work. We agree with the reviewer that both these models integrate GNN and flow methods, which could be considered as key contributions of these two models. We are happy to discuss the differences between the models, but we are not claiming full contributions over GNF. \n\n*Detailed questions\nQ1. GNF uses different input data\n- The full model proposed by Liu et al(2019) consists of an autoencoder and normalizing flow with graphs as a novel and powerful architecture for handling graph generation task. We are comparing with their full model. We apologize for the confusion and we have clarified that in the table. \n- This model in the paper uses coupling layers which requires the input data to have dimension higher than one for splitting. In contrast, our model CGF can handle both one-dimensional and higher dimensional data. \n- Moreover, while the representations are not the same, the task remains the same (i.e., generating diverse graphs) and we compute the metrics on the output of the model irrespective of the model being used to represent the value of the input graph variables.\n\nQ2. Dual graph\nThank you for pointing out. We changed the term dual graph to line graph and describe the transformation performed on the graph as edges being switched to nodes and nodes to edges. We\u2019ve made these changes in the paper.\n\nQ3. Baselines for table 2 and table 3\nThe baselines are all state-of-the-art structured and unstructured latent space baseline models \u2014 all published in the timeline 2016-2019. Our method is effective because it integrates powerful flow models for graph-structured data, and eliminate the assumptions over latent distributions (Gaussian, etc.).\n\n[1] Augmented Neural ODEs, Emilien Dupont \u00b7 Arnaud Doucet \u00b7 Yee Whye Teh, NeurIPS 2019\n[2] Neural Jump Stochastic Differential Equations, Junteng Jia \u00b7 Austin Benson, NeurIPS 2019\n"}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values-dropdown": ["everyone", "ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/AnonReviewer.*", "ICLR.cc/2020/Conference/Paper1101/Reviewers/Submitted", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response"}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+|ICLR.cc/2020/Conference/Paper1101/Authors|ICLR.cc/2020/Conference/Paper1101/Area_Chair[0-9]+|ICLR.cc/2020/Conference/Program_Chairs"}}, "readers": ["everyone"], "tcdate": 1569504161241, "tmdate": 1576860536967, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment"}}}, {"id": "H1xMx907jH", "original": null, "number": 3, "cdate": 1573280233867, "ddate": null, "tcdate": 1573280233867, "tmdate": 1573329170768, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "SkgZi5y0Yr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment", "content": {"title": "Response to Reviewer #3", "comment": "We would like to thank the reviewer for valuable comments and suggestions on our manuscript. We updated the manuscript and changes are marked by red color.\n\nQ1.1 Motivation of dual Graph.\nClarification on the dual graph: We would like to clarify that the term dual graph that we previously used is confusing. We have corrected the term \u201cdual graph\u201d to \u201cline graph\u201d. This line graph is obtained by transforming the original graph with edges being switched to nodes and nodes to edges.\n\nQ1.2 The experiment on Graph Generation is not clear to me. What is the motivation of using the dual of the graph? \nCGF operates over graph nodes (variables). The task of graph generation requires modeling of edges as variables (e.g. generating the adjacency matrix). Therefore, we transform the input graph G=(V, E) to line graph G\u2019=(V\u2019, E\u2019) and use CGF to directly model nodes in the line graph G\u2019. V\u2019 corresponds to E in the original graph G and E\u2019 is determined by the nodes V in the original graph G.\n\nQ1.3 What is the input to the full-connected layers? Is the input dimension N^2?\nThe input to the CGF is the node variables V\u2019 from the line graph. It takes value either 0 or 1, representing non-existence or existence. The input dimension to the model is N^2 (N is number of nodes ).The fully connected layers are message functions and used for local message passing between variables.\n\nQ2. How does the proposed method scale with the graph size? \nOur CGF model scales with number of dimensions similar to FFJORD or NeuralODE. We would like to mention that although the ODE equations involving independent variables linearly scale with number of nodes. However, in the case of the graph-structured variables, they are solved collectively instead of solving them independently. Relying on graph message passing will lead to better modeling of each node and potentially lessen the computation time. \nThank you for the suggestion. We analyzed the number of function evaluation w.r.t graph size on graph generation problem. The plots are updated in Appendix under A5. The plots show that the number of function evaluations (steps to solve ode) doesn\u2019t linearly increase with the increment in number of nodes.\n\nQ3. Experiments on larger graphs\nOur model is generating entire graphs with a single feed-forward pass. Since our focus is on expressiveness of graph generative models, we show the potential of our model to generate graphs on small-scale graph datasets (Community-small and Ego-small). These are the established benchmark datasets for evaluating single feed-forward pass methods as done in [1,2]. \nOur model could potentially be extended to larger graphs by employing autoregressive (i.e.,generating K nodes at a time) or multiscale schemes.\n\n\n[1] GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders, Martin Simonovsky, Nikos Komodakis, arXiv, 2018\n[2] Graph Normalizing Flow, Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky, arXiv, 2018"}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values-dropdown": ["everyone", "ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/AnonReviewer.*", "ICLR.cc/2020/Conference/Paper1101/Reviewers/Submitted", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response"}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+|ICLR.cc/2020/Conference/Paper1101/Authors|ICLR.cc/2020/Conference/Paper1101/Area_Chair[0-9]+|ICLR.cc/2020/Conference/Program_Chairs"}}, "readers": ["everyone"], "tcdate": 1569504161241, "tmdate": 1576860536967, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment"}}}, {"id": "SylErbrzoS", "original": null, "number": 7, "cdate": 1573175611651, "ddate": null, "tcdate": 1573175611651, "tmdate": 1573175611651, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "B1xZgPNbsH", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment", "content": {"title": "Also dual graph is not the correct term to use here", "comment": "In graph theory dual graph has a different meaning.\nThe correct term to use here is Line graph (or edge-to-vertex dual graph) [Gross and Yellen 2006]."}, "signatures": ["~Mr_Reviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["~Mr_Reviewer1", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "User groups that will be able to read this comment."}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "~.*"}}, "readers": ["everyone"], "tcdate": 1569504199575, "tmdate": 1576860570725, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment"}}}, {"id": "ByeLVtNWiS", "original": null, "number": 6, "cdate": 1573108014407, "ddate": null, "tcdate": 1573108014407, "tmdate": 1573108014407, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment", "content": {"title": "My third question regarding the performance of the proposed method on the puzzle generation task", "comment": "There are huge discrepancy between patches in each generated puzzle in Figure 3. It seems as if patches are generated independently of each other without passing any information among them. \nI was hoping to see an ablation study on the graph structure. For example, what happens if none of the nodes (patches) in the graph are connected? Or in the opposite case, what happens if all the nodes are connected?\nIf the method actually works, I would expect to see more similarity between patches in the generated puzzles when there are connections between nodes and less similarity when there's no connection.\nAlso, what would be the NLL in those cases? Is Continuous Graph Flow actually capable of performing message passing?\n\nSuch ablation study with both qualitative and quantitative results are necessary.\n\nAlso, I wonder if a simple generative model (e.g. VAE, Flow, etc) that is trained on each patch and conditioned on the index of each patch ( top-left: 1, top-middle: 2, etc) would produce better results (NLL) than this method or not. (P(x_i | i) where x_i is a patch and i is the index of that patch. Then log-likelihood of a generated puzzle would be \\Sum_{i=1}^9 P(x_i | i) ).\n\n\n"}, "signatures": ["~Mr_Reviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["~Mr_Reviewer1", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "User groups that will be able to read this comment."}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "~.*"}}, "readers": ["everyone"], "tcdate": 1569504199575, "tmdate": 1576860570725, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment"}}}, {"id": "B1xZgPNbsH", "original": null, "number": 5, "cdate": 1573107432840, "ddate": null, "tcdate": 1573107432840, "tmdate": 1573107432840, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment", "content": {"title": "My second question regarding the vague experimental section", "comment": "What does DEGREE, CLUSTERING, and ORBIT mean in the graph generation section?\nThese words (degree, clustering, and orbit) are only mentioned in Table 1 and there're no explanations of these in the text. I believe this task (graph generation) and the criteria for comparison deserve a short description, even if it is following the same experimental setup as GNF.\n\nWhy lower Orbit is better? Why lower Clustering is better? etc."}, "signatures": ["~Mr_Reviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["~Mr_Reviewer1", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "User groups that will be able to read this comment."}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "~.*"}}, "readers": ["everyone"], "tcdate": 1569504199575, "tmdate": 1576860570725, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment"}}}, {"id": "H1luoS4bsS", "original": null, "number": 4, "cdate": 1573107103682, "ddate": null, "tcdate": 1573107103682, "tmdate": 1573107103682, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "Hkgp-7dstr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment", "content": {"title": "Thank you for the response -- Clarifying my concern", "comment": "Here's the first question:\n\nIn one set of experiments the following baselines are chosen to be compared against the proposed method\n- GraphVAE\n- DeepGMG\n- GraphRNN\n- GNF\n\nIn another set of experiments these baselines are chosen to be compared against the proposed method:\n- BiLSTM + VAE \n- StructuredVAE\n- Graphite\n- VMP-SIN\n- GAE\n- NRI\n\nThe problem is that there's no intersection between these set of baselines. Why? \nDoes this mean that the proposed method could only beat some of the baselines in each task but not all? So only those with lower performance than the proposed method are included in the tables?\nIn any case, this kind of experimental setup seems so weird to me, except there's a very particular reason for this choice of baselines.\n"}, "signatures": ["~Mr_Reviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["~Mr_Reviewer1", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "User groups that will be able to read this comment."}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "~.*"}}, "readers": ["everyone"], "tcdate": 1569504199575, "tmdate": 1576860570725, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment"}}}, {"id": "BkgReQ9aKB", "original": null, "number": 1, "cdate": 1571820277909, "ddate": null, "tcdate": 1571820277909, "tmdate": 1572972512789, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review", "content": {"experience_assessment": "I have read many papers in this area.", "rating": "3: Weak Reject", "review_assessment:_thoroughness_in_paper_reading": "I read the paper thoroughly.", "review_assessment:_checking_correctness_of_experiments": "I assessed the sensibility of the experiments.", "title": "Official Blind Review #1", "review_assessment:_checking_correctness_of_derivations_and_theory": "N/A", "review": "This paper proposes continuous graph flow (CGF), a flow-based generative model for graphs. Based on the idea to build continuous-time flows with neural ODEs, the node features are transformed into Gaussian random variables via message passing. The log-likelihood can be approximated stochastically.\n\nI find it hard to assess the novelty of this work because 1) the algorithm looks like a trivial application of continuous-time normalizing flow to graph data using message passing algorithm, and 2) the concurrent work graph normalizing flow (GNF, Liu et al., 2019). I failed to find any algorithmic innovation more than a mere application of continuous-time flow to graph data. The very idea of a flow-based model for graphs using the message passing algorithm may be considered as a contribution, but this is also blurred because of the concurrent work GNF. \n\nThe experiments look interesting, but there are some minor concerns. For the unsupervised graph generation task, CGF is shown to perform better than GNF, but I think the comparison here may not be fair because the results for GNF seem to be obtained from the paper uses a different way to construct initial node features to be fed into message passing. Specifically, according to the GNF paper, they inject an i.i.d. Gaussian noise as initial node features, but this work uses different schemes based on the dual graph (btw I think the term dual graph may be misleading. There already exists a common term called dual-graph with different definition). So I think to compare the expressive power of flows, it would be fair to start from a common scheme to build initial node features. GNF should also be compared to CGF for the other experiments. Seems like the baselines presented in Table 2 and Table 3 are quite dumb baselines not well suited for the tasks considered here. \n\nIn page 2, the authors stated that \"GNF involves partitioning of data dimensions into two halves and employs coupling layers to couple them back. This leads to several constraints on function forms and model architectures...\". I think GNF can be improved using more advanced transformation other than affine coupling, such as recently proposed mixture logistic CDF [1] or neural spline flow [2]. Continuous-time flow may still have an advantage in memory usage, but at least in terms of expressive power, I think it is not clear whether CGF is particularly better.\n\n[1] Ho et al., Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design, 2019\n[2] Durkan et al., Neural Spline Flows, 2019"}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"experience_assessment": {"required": true, "order": 4, "description": "Please make a selection that represents your experience correctly", "value-radio": ["I have published in this field for several years.", "I have published one or two papers in this area.", "I have read many papers in this area.", "I do not know much about this area."]}, "rating": {"value-dropdown": ["1: Reject", "3: Weak Reject", "6: Weak Accept", "8: Accept"], "order": 3, "required": true}, "review_assessment:_checking_correctness_of_experiments": {"required": true, "order": 7, "description": "If no experiments, please select N/A", "value-radio": ["I carefully checked the experiments.", "I assessed the sensibility of the experiments.", "I did not assess the experiments.", "N/A"]}, "review_assessment:_thoroughness_in_paper_reading": {"required": true, "order": 5, "description": "If this is not applicable, please select N/A", "value-radio": ["I read the paper thoroughly.", "I read the paper at least twice and used my best judgement in assessing the paper.", "I made a quick assessment of this paper.", "N/A"]}, "title": {"value-regex": "Official Blind Review #[0-9]+", "order": 1, "required": true, "description": "Please replace NUM with your AnonReviewer number (it is the number following \"AnonReviewer\" in your signatures below)", "default": "Official Blind Review #NUM"}, "review": {"value-regex": "[\\S\\s]{500,200000}", "order": 2, "description": "Provide your complete review here (500 - 200000 characters). For guidance in writing a good review, see this brief reviewer guide (https://iclr.cc/Conferences/2020/ReviewerGuide) with three key bullet points.", "required": true}, "review_assessment:_checking_correctness_of_derivations_and_theory": {"required": true, "order": 6, "description": "If no derivations or theory, please select N/A", "value-radio": ["I carefully checked the derivations and theory.", "I assessed the sensibility of the derivations and theory.", "I did not assess the derivations or theory.", "N/A"]}}, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "Select all user groups that should be able to read this comment."}, "nonreaders": {"values": []}, "writers": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1575832786691, "duedate": 1572706740000, "multiReply": false, "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Reviewers"], "noninvitees": [], "tcdate": 1570237742362, "tmdate": 1575832786703, "super": "ICLR.cc/2020/Conference/-/Official_Review", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review"}}}, {"id": "SkgZi5y0Yr", "original": null, "number": 2, "cdate": 1571842713115, "ddate": null, "tcdate": 1571842713115, "tmdate": 1572972512746, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review", "content": {"experience_assessment": "I have published one or two papers in this area.", "rating": "3: Weak Reject", "review_assessment:_thoroughness_in_paper_reading": "I made a quick assessment of this paper.", "review_assessment:_checking_correctness_of_experiments": "I assessed the sensibility of the experiments.", "title": "Official Blind Review #3", "review_assessment:_checking_correctness_of_derivations_and_theory": "N/A", "review": "The paper presents a method to do Continuous Normalizing Flow for graphs by defining the density evolution via ODEs over shared variables. Continous message passing scheme introduced can leverage the free-form model architectures which allow flexibility in handling variable data dimensions. The results of three different generation tasks indicate improved performance over the baseline methods. \n\nNovelty: The basic methodological contribution of the paper seems somewhat limited. The main idea of the paper follows directly from NeuralODE (Chen et al., 2018) and FFJord (Grathwohl et al., 2019). Nevertheless, I do agree that adapting the NeuralODEs and continuous flows for unstructured data is challenging and deserves its own analysis. However, I find the experiment section to be not very clear (See specific comments below). \n\nRecommendation: Weak Reject\n\nConcerns: \n\n- The experiment on Graph Generation is not clear to me. What is the motivation of using the dual of the graph? What is the input to the full-connected layers? Is the input dimension N^2 (the number of edges)? Please clarify. It would be helpful if the implementation details in Appendix A.1 can be formalized in the main paper since this is the main contribution of the paper. Overall the experiment section in the main paper lacks sufficient details to comment on the efficacy of the method.\n \n- NeuralODEs involve iterative numerical solvers which can be very slow. It seems that the proposed method involves simultaneously solving ODEs that linearly scale with the number of nodes (Equation 11)? I think there should be some analysis of how the proposed method scales with the graph size. I am not sure if NeuralODE would perform well when the number of nodes is large.\n\n- Compared to other baseline methods (see You et al. 2018), the datasets used for analysis are smaller versions of the original datasets. There are other datasets that can be used for experiments on graph generation: See Grid, Protein "}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer3"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer3"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"experience_assessment": {"required": true, "order": 4, "description": "Please make a selection that represents your experience correctly", "value-radio": ["I have published in this field for several years.", "I have published one or two papers in this area.", "I have read many papers in this area.", "I do not know much about this area."]}, "rating": {"value-dropdown": ["1: Reject", "3: Weak Reject", "6: Weak Accept", "8: Accept"], "order": 3, "required": true}, "review_assessment:_checking_correctness_of_experiments": {"required": true, "order": 7, "description": "If no experiments, please select N/A", "value-radio": ["I carefully checked the experiments.", "I assessed the sensibility of the experiments.", "I did not assess the experiments.", "N/A"]}, "review_assessment:_thoroughness_in_paper_reading": {"required": true, "order": 5, "description": "If this is not applicable, please select N/A", "value-radio": ["I read the paper thoroughly.", "I read the paper at least twice and used my best judgement in assessing the paper.", "I made a quick assessment of this paper.", "N/A"]}, "title": {"value-regex": "Official Blind Review #[0-9]+", "order": 1, "required": true, "description": "Please replace NUM with your AnonReviewer number (it is the number following \"AnonReviewer\" in your signatures below)", "default": "Official Blind Review #NUM"}, "review": {"value-regex": "[\\S\\s]{500,200000}", "order": 2, "description": "Provide your complete review here (500 - 200000 characters). For guidance in writing a good review, see this brief reviewer guide (https://iclr.cc/Conferences/2020/ReviewerGuide) with three key bullet points.", "required": true}, "review_assessment:_checking_correctness_of_derivations_and_theory": {"required": true, "order": 6, "description": "If no derivations or theory, please select N/A", "value-radio": ["I carefully checked the derivations and theory.", "I assessed the sensibility of the derivations and theory.", "I did not assess the derivations or theory.", "N/A"]}}, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "Select all user groups that should be able to read this comment."}, "nonreaders": {"values": []}, "writers": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1575832786691, "duedate": 1572706740000, "multiReply": false, "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Reviewers"], "noninvitees": [], "tcdate": 1570237742362, "tmdate": 1575832786703, "super": "ICLR.cc/2020/Conference/-/Official_Review", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review"}}}, {"id": "Byxc74-0Yr", "original": null, "number": 3, "cdate": 1571849250060, "ddate": null, "tcdate": 1571849250060, "tmdate": 1572972512703, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review", "content": {"experience_assessment": "I have read many papers in this area.", "rating": "3: Weak Reject", "review_assessment:_thoroughness_in_paper_reading": "I read the paper at least twice and used my best judgement in assessing the paper.", "review_assessment:_checking_correctness_of_experiments": "I assessed the sensibility of the experiments.", "title": "Official Blind Review #2", "review_assessment:_checking_correctness_of_derivations_and_theory": "I did not assess the derivations or theory.", "review": "This paper proposes a new variant of invertible flow-based model for graph structured data. \nSpecifically, the authors proposed a continuous normalizing flow model for graph generation, first in the graph generation literature. \nThe authors claim that the free-form model architecture of neural ODE formulation of continuous flow is advantageous against standard discrete flow models. Experimental results show that the proposed model is superior to recent models in image puzzling and layout generation datasets. \n\nOverall, manuscript is well organized. \nThe combination of continuous flows and graph structured data is new in the literature (as far as I know). Proposed formulation seems natural and reasonable. I find no fatal flows in the formulation. In experiments, the proposed model achieved good scores against recent GNN works. \n\nConcerning the existing invertible flow-based models for graph structured data, Madhawa\u2019s work is one of the first attempts in the literature. I think the paper below should be refereed appropriately: \nMadhawa+, \u201cGraph NVP\u201d, arXiv: 1905.11600, 2019. \n\nThe way of incorporating relational structure into flows are very similar to the GraphNVP and Graph Normalizing Flow: using neighboring nodes\u2019 hidden vectors as parameters (or input to parameter inference networks). \nIn addition, I found no special tricks or theoretical considerations to achieve the continuous flow for graphs. Based on these points, I think technical contribution of this paper is somewhat limited. \n\nI cannot find information about the specific chosen forms of f-hat and g in Eq.(10) within the manuscript. Are the choices of f-hat and g are crucial for performance? It is preferable if the authors can present any experimental validations concerning this issue. \n\nMy main concerns are in the experimental section. \n\nI\u2019m not fully convinced in the necessity of the continuous normalizing flows for the experimental tasks. None of the experimental tasks have `````'' intrinsic continuous time dynamics over graph-structured data (Sec. 2)''. Then, what is the rationale to adopt Continuous graph flow for these tasks? \n\nOne reason to adopt continuous flows is that the ODE formulation allows users to choose free-form model architecture, yielding more complicated mappings to capture delicate variable distributions. \nI expect some assessments are made concerning this issue. My suggestion is (i) to test the discretized model of the proposed Continuous Graph Flow and see how the discretization deteriorate the performance, and (ii) to test several choices of f-hat and g (Eq.10) to show the necessity of ODE formulation, accommodating free-form model architecture. \n\nIn the current manuscript, Graph Normalizing Flow (GNF) is the closest competitor. However, GNF is not tested in the puzzle and the scene graph experiments. Why is that?\n\nI\u2019d like to hear opinions of the authors concerning these issues, and hope some discussions are included in the manuscript. \n\n\nSummary\n+ continuous normalizing flow is first applied to graph structure data\n+ manuscript is well organized\n+- natural and reasonable formulation. But at the same time, technological advancement is limited. \n- Less convinced to adopt continuous flow for graph-structured data without no intrinsic continuous dynamics. \n- Necessity or advantages of ``continuous\u2019\u2019 flows are not well assessed in the experiments. Please consider some additional assessments suggested in the review comment. \n- GNF, the closest competitor, is omitted in the 2d and the 3rd experiments. No explanations about this. "}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer2"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/AnonReviewer2"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"experience_assessment": {"required": true, "order": 4, "description": "Please make a selection that represents your experience correctly", "value-radio": ["I have published in this field for several years.", "I have published one or two papers in this area.", "I have read many papers in this area.", "I do not know much about this area."]}, "rating": {"value-dropdown": ["1: Reject", "3: Weak Reject", "6: Weak Accept", "8: Accept"], "order": 3, "required": true}, "review_assessment:_checking_correctness_of_experiments": {"required": true, "order": 7, "description": "If no experiments, please select N/A", "value-radio": ["I carefully checked the experiments.", "I assessed the sensibility of the experiments.", "I did not assess the experiments.", "N/A"]}, "review_assessment:_thoroughness_in_paper_reading": {"required": true, "order": 5, "description": "If this is not applicable, please select N/A", "value-radio": ["I read the paper thoroughly.", "I read the paper at least twice and used my best judgement in assessing the paper.", "I made a quick assessment of this paper.", "N/A"]}, "title": {"value-regex": "Official Blind Review #[0-9]+", "order": 1, "required": true, "description": "Please replace NUM with your AnonReviewer number (it is the number following \"AnonReviewer\" in your signatures below)", "default": "Official Blind Review #NUM"}, "review": {"value-regex": "[\\S\\s]{500,200000}", "order": 2, "description": "Provide your complete review here (500 - 200000 characters). For guidance in writing a good review, see this brief reviewer guide (https://iclr.cc/Conferences/2020/ReviewerGuide) with three key bullet points.", "required": true}, "review_assessment:_checking_correctness_of_derivations_and_theory": {"required": true, "order": 6, "description": "If no derivations or theory, please select N/A", "value-radio": ["I carefully checked the derivations and theory.", "I assessed the sensibility of the derivations and theory.", "I did not assess the derivations or theory.", "N/A"]}}, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "Select all user groups that should be able to read this comment."}, "nonreaders": {"values": []}, "writers": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1575832786691, "duedate": 1572706740000, "multiReply": false, "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Reviewers"], "noninvitees": [], "tcdate": 1570237742362, "tmdate": 1575832786703, "super": "ICLR.cc/2020/Conference/-/Official_Review", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Review"}}}, {"id": "Hkgp-7dstr", "original": null, "number": 1, "cdate": 1571681029216, "ddate": null, "tcdate": 1571681029216, "tmdate": 1571681029216, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "rylhIt7wKS", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment", "content": {"title": "Thank you for your interest and comments", "comment": "We thank the Anonymous Reader for the interest in our paper. However, we don't quite understand the comment especially on experiments since there are no specific concerns listed. We are happy to provide more information but we are not sure which parts are unclear.\n\nRegarding comparisons, to clarify, Graph Normalizing Flows by Liu et al(2019) is a concurrent work (as mentioned in Intro) rather than a standard baseline. We take the quantitative results for graph generation directly from their paper for reference only and follow the same evaluation protocol to conduct experiments for our proposed model."}, "signatures": ["ICLR.cc/2020/Conference/Paper1101/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values-dropdown": ["everyone", "ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/AnonReviewer.*", "ICLR.cc/2020/Conference/Paper1101/Reviewers/Submitted", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response"}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "ICLR.cc/2020/Conference/Paper1101/AnonReviewer[0-9]+|ICLR.cc/2020/Conference/Paper1101/Authors|ICLR.cc/2020/Conference/Paper1101/Area_Chair[0-9]+|ICLR.cc/2020/Conference/Program_Chairs"}}, "readers": ["everyone"], "tcdate": 1569504161241, "tmdate": 1576860536967, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Official_Comment"}}}, {"id": "rylhIt7wKS", "original": null, "number": 3, "cdate": 1571400020066, "ddate": null, "tcdate": 1571400020066, "tmdate": 1571400020066, "tddate": null, "forum": "BkgZSCEtvr", "replyto": "BkgZSCEtvr", "invitation": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment", "content": {"comment": "Since on the theoretical side there is only incremental contribution, it's necessary to have a stronger experimental results. Thus it's necessary to see the superiority of this method in a correct set of experiments. I have read through the experimental section at least 3 times and still many of the things don't make sense to me.\n\nOne important question is, why the authors compared their method with different set of baselines in each task?\nI think the GraphNormalizingFlow (Liu et al., 2019) is an important baseline and should be included in all the experiments. It is not clear why this method is not included in the puzzle/layout generation tasks. ", "title": "Incremental contribution and a very very vague experimental section"}, "signatures": ["~Anonymous_Reader2"], "readers": ["everyone"], "nonreaders": [], "writers": ["~Anonymous_Reader2", "ICLR.cc/2020/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Continuous Graph Flow", "authors": ["Zhiwei Deng", "Megha Nawhal", "Lili Meng", "Greg Mori"], "authorids": ["zhiweid@princeton.edu", "mnawhal@sfu.ca", "lilimeng1103@gmail.com", "mori@cs.sfu.ca"], "keywords": ["graph flow", "normalizing flow", "continuous message passing", "reversible graph neural networks"], "TL;DR": "Graph generative models based on generalization of message passing to continuous time using ordinary differential equations ", "abstract": "In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a probability density over the random variables represented by the graph. It is formulated as an ordinary differential equation system with shared and reusable functions that operate over the graphs. This leads to a new type of neural graph message passing scheme that performs continuous message passing over time. This class of models offers several advantages: a flexible representation that can generalize to variable data dimensions; ability to model dependencies in complex data distributions; reversible and memory-efficient; and exact and efficient computation of the likelihood of the data. We demonstrate the effectiveness of our model on a diverse set of generation tasks across different domains: graph generation, image puzzle generation, and layout generation from scene graphs. Our proposed model achieves significantly better performance compared to state-of-the-art models.", "pdf": "/pdf/340192db2a28ff7029a2bae975c0e386912d7888.pdf", "paperhash": "deng|continuous_graph_flow", "original_pdf": "/attachment/a749a6e3130acf2dd20b5c9848320d62cc37865d.pdf", "_bibtex": "@misc{\ndeng2020continuous,\ntitle={Continuous Graph Flow},\nauthor={Zhiwei Deng and Megha Nawhal and Lili Meng and Greg Mori},\nyear={2020},\nurl={https://openreview.net/forum?id=BkgZSCEtvr}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"required": true, "description": "Brief summary of your comment.", "order": 0, "value-regex": ".{1,500}"}, "comment": {"required": true, "description": "Your comment or reply (max 5000 characters). Add TeX formulas using the following formats: $In-line Formula$ or $$Block Formula$$", "order": 1, "value-regex": "[\\S\\s]{1,5000}"}}, "forum": "BkgZSCEtvr", "readers": {"values": ["everyone"], "description": "User groups that will be able to read this comment."}, "writers": {"values-copied": ["ICLR.cc/2020/Conference", "{signatures}"]}, "signatures": {"description": "How your identity will be displayed.", "values-regex": "~.*"}}, "readers": ["everyone"], "tcdate": 1569504199575, "tmdate": 1576860570725, "super": "ICLR.cc/2020/Conference/-/Comment", "signatures": ["ICLR.cc/2020/Conference"], "writers": ["ICLR.cc/2020/Conference"], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2020/Conference/Paper1101/Authors", "ICLR.cc/2020/Conference/Paper1101/Reviewers", "ICLR.cc/2020/Conference/Paper1101/Area_Chairs", "ICLR.cc/2020/Conference/Program_Chairs"], "id": "ICLR.cc/2020/Conference/Paper1101/-/Public_Comment"}}}], "count": 14} |
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{
"ID": "143",
"post_author": "130",
"post_date": "2006-01-07 23:44:24",
"post_date_gmt": "2006-01-08 04:44:24",
"post_content": "I've come to realize that in user interfaces (whether digital or physical) its often the subtleties that make most of the difference. The best of these are details which you use without realizing or without prior knowledge. Simple examples are right clicking on an object to see what you can \"do\" with it or using page up/down in some application (like a photo app) without taking the time to think \"I wonder if page up will move to the previous picture\" -- it's when you try something and then realize (afterward) that you did it by native reflex, without thought at all.\r\n\r\nUnfortunately, there is a problem with getting excited about stumbling on seamlessly intuitive UI features. You are prone to get frustrated when those things \"that should just work\" don't work. :)\r\n\r\nToday's example of that is clicking a link while visiting a web page. Its not every time you click a link, but those times when you realize \"oh crap, I didn't want to click on that... now I have to rush really quickly to try and hit the stop button before the next page loads (and man is that stop button small)\". What I tried today is clicking on the link again after realizing I didn't want to go to that page. I think my mind tried this since there are many hide/open ui patterns in many of the new AJAX websites. My mind must have jumped and tried out that same pattern in this (different) situation, but alas -- it doesn't work.\r\n\r\nSo this is where I say \"Why not?\"\r\n\r\nAnd now this is the point where I realize my intention of just mentioning a tiny ui feature is blown out of proportion by me doing all of this extraneous explanation.\r\n\r\nSo yea, its a small thing but at least I think it would be useful.\r\n\r\nSo while I'm on this topic another small ui gesture I'd love to have is feed readers (news aggregators/whatever name is in vogue now) that display the length of a post alongside the title. Maybe it's a number of paragraphs, maybe it's a small icon to represent the long posts, maybe it's some representative color gradient. All it has to do is give me some blurry impression whether the post is \"more longish\" or \"more shortish\". That could makes broswing/flipping though feeds much, much easier. If its a feed that I'm only semi interested in then I can just skip over the long ones. (I guess I'm the kind of person that feels guilty stopping reading something halfway through). Ever since my feed reader has gone out of control (I spent much of today trying to work on this) I've had to start breezing though all the \"possibly less interesting\" entries instead of reading everything (in addition to dropping the blogs I just never got around to).\r\n\r\nThe reason I'm making such a deal about these simple touches is that I really do think they make quite a large difference when amortized over the long term. (oh yea, and also if enough people hear about it and become interested they might get the motivation to write feature requests for me) :)\r\n\r\nOh.. just one more thing. Will <a title=\"rememberthemilk\" href=\"http://www.rememberthemilk.com/home/timmfin/\">rememberthemilk</a> please show the number of tasks along/inside each tab? Pretty please?",
"post_title": "The little things...",
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"post_name": "143",
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"post_modified": "2006-01-09 22:17:10",
"post_modified_gmt": "2006-01-10 03:17:10",
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{
"body": {
"1": {
"main": "産業労働者住宅資金融通法第七条の規定による貸付金の一戸当たりの金額の限度及び償還期間を定める政令\n（昭和四十八年政令第百三十三号）本則の表償還期間の欄に規定する内閣府令・財務省令で定める基準は次に掲げるものとする。",
"enum": {
"1": "建築基準法施行令\n（昭和二十五年政令第三百三十八号）第百十五条の二の二第一項第一号\nに掲げる技術的基準に適合すること。",
"2": "構造耐力上主要な部分（建築基準法施行令第一条第三号\nに規定する構造耐力上主要な部分をいう。以下同じ。）が、次のイ又はロに掲げる基準に適合すること。イ 構造耐力上主要な部分である壁、柱及び横架材の全部又は一部を木造とする住宅（ロに掲げるものを除く。）にあっては、木造であるすみ柱の張り間方向及びけた行方向の小径は、十二センチメートル（階数が二以上の住宅における通し柱であるすみ柱（すぎ、ひのき、ひばその他これらと同等以上の耐久性を有するものとして沖縄振興開発金融公庫が指定する建築材料又は直接外気に接する構造であることその他これと同等以上の耐久性を有するものとして沖縄振興開発金融公庫が指定する構造方法によるものを除く。）にあっては、十三・五センチメートル）以上であり、かつ、構造耐力上主要な部分にあって木造以外の構造である壁、柱及び横架材は、耐火構造であること。\nロ 構造耐力上主要な部分の全部又は一部に枠組壁工法（木材で組まれた枠組みに構造用合板その他これに類するものを打ち付けた床及び壁により建築物を建築する工法をいう。以下この号において同じ。）を用いる住宅にあっては、枠組壁工法を用いる部分である外壁の下地の材料は、屋外に面する部分又は常温湿潤の状態となるおそれのある部分に用いる構造用合板であって日本農林規格に適合するもののうち、厚さ九ミリメートル以上のものその他これと同等以上の耐久性を有するものとして沖縄振興開発金融公庫が指定する規格に適合するものであり、かつ、構造耐力上主要な部分であって枠組壁工法以外の工法を用いる部分である壁、柱及び横架材は、耐火構造であること。",
"3": "基礎は一体の鉄筋コンクリート造の布基礎とし、地盤面からその上端までの高さは四十センチメートル以上であること。",
"4": "小屋裏の壁で屋外に面するもの又は軒裏には、換気上有効な位置に二以上の換気孔を設けるものとし、換気孔の有効面積の天井の面積に対する割合は、原則として三百分の一以上とすること。",
"5": "外壁の床下部分には、壁の長さ四メートル以下ごとに、有効面積三百平方センチメートル以上の換気孔を設け、床下はコンクリート、防湿フィルムその他これらに類する材料で覆うこと。",
"6": "浴室、窓を有しない便所その他の湿気の滞留するおそれのある部分には、給気口及び排気機その他の換気上有効な換気設備を設けること。",
"7": "給水、排水その他の配管設備（配電管を除く。）で各戸に共用のものは、構造耐力上主要な部分である壁の内部に設けないこと。",
"8": "前各号に定めるもののほか、住宅の各部分は、耐久上支障のない措置を講じたものであること。"
}
},
"1(2)": {
"main": "建築材料又は構造方法により、前項の規定により難い部分のある住宅であって、前項の基準に該当する住宅と同等以上の耐久性を有すると認められる住宅については、沖縄振興開発金融公庫は、産業労働者住宅資金融通法第七条\nの規定による貸付金の一戸当たりの金額の限度、利率及び償還期間を定める政令本則の表償還期間の欄に規定する内閣府令・財務省令で定める基準に該当する耐久性を有する住宅とすることができる。",
"enum": {
}
},
"2": {
"main": "沖縄振興開発金融公庫から貸付けを受けた者（包括承継人を含む。）で産業労働者住宅資金融通法第七条第一項第三号\nの規定に該当するものが当該貸付金に係る住宅を賃貸する場合においては、沖縄振興開発金融公庫法施行規則\n（昭和四十七年総理府・大蔵省令第一号）第五条\nから第九条\nまで（第五条第一項第一号及び第二項第一号を除く。）、第十条第三項、第十一条の二、第十二条の二第一項及び第十四条の規定（当該貸付けに係る住宅の戸数が二十戸未満である場合その他沖縄振興開発金融公庫が適当と認める場合においては、第六条から第九条まで及び第十条第三項の規定を除く。）は、産業労働者住宅資金融通法第十三条の二第一項\nの主務省令で定める基準、同条第二項\nの主務大臣が定める額及び同条第三項\nの主務省令で定める基準について準用する。この場合において、第五条第一項中「法第十九条第一項第三号の規定による貸付けを受けた者で同号ハの規定に該当するもの」とあるのは「沖縄振興開発金融公庫から貸付けを受けた者で産業労働者住宅資金融通法第七条第一項第三号\nの規定に該当するもの」と、「同号\nハ（１）」とあるのは「同号\nイ」と、同条第二項第二号\n中「居住し、又は勤務する場所」とあるのは「住所又は事業場」と、第五条の二中「法第十九条第一項第三号の規定による貸付金に係る住宅を同号ハ（２）に掲げる者」とあるのは「産業労働者住宅資金融通法第七条第一項\nの規定による貸付金に係る住宅を同項第三号\nロに掲げる者」と、第十一条の二中「法第十九条第一項第三号」とあるのは「産業労働者住宅資金融通法第七条第一項\n」と、「第五条、前六条、次条及び第十二条の二の規定」とあるのは「第五条（第一項第一号及び第二項第一号を除く。）、第六条から第九条まで、第十条第三項、第十二条の二第一項及び第十四条の規定（当該貸付けに係る住宅の戸数が二十戸未満である場合その他沖縄振興開発金融公庫が適当と認める場合においては、第六条から第九条まで及び第十条第三項の規定を除く。）」と、第十二条の二第一項中「法第三十五条第三項」とあるのは「産業労働者住宅資金融通法第十三条の二第三項\n」と、第十四条の見出し及び同条第一項中「合理的土地利用耐火建築物等内の住宅」とあるのは「住宅」と、同条第一項中「令第一条第一項第八号又は第九号に規定する資金の貸付け」とあり、同条第二項中「令第一条の二第一項第八号又は第九号の規定による貸付け」とあり、及び同条第四項中「令第一条の二第一項第八号又は第九号の規定による貸付金」とあるのは「産業労働者住宅資金融通法第七条第一項\nの規定による貸付けのうち同項第三号\nに掲げる者に対するもの」と、同条第一項\n中「含む。以下「合理的土地利用耐火建築物等内住宅賃貸人」という。」とあるのは「含む。」と、同条第一項第一号\n、第二項及び第三項中「合理的土地利用耐火建築物等内住宅賃貸人」とあるのは「賃貸人」と読み替えるものとする。",
"enum": {
}
},
"2(2)": {
"main": "賃貸人は、前項において準用する沖縄振興開発金融公庫法施行規則第九条\nの規定により賃借人を選定しようとする場合においては、沖縄労働局長の意見を参酌しなければならない。",
"enum": {
}
},
"3": {
"main": "沖縄振興開発金融公庫から貸付けを受けた者（包括承継人を含む。）で産業労働者住宅資金融通法第七条第一項第四号\nの規定に該当するものが当該貸付金に係る住宅、土地又は借地権を譲渡する場合においては、沖縄振興開発金融公庫法施行規則第十六条\n（第二項第一号を除く。）、第十八条から第二十一条まで（第二十条第一項第三号を除く。）、第二十二条第一項、第二十四条第三項、第二十五条、第二十六条、第二十八条及び第二十九条（第一項第三号及び第四号を除く。）の規定を準用する。この場合において、第十六条第一項中「法第十九条第一項第三号の規定による貸付けを受けた者で同号ニの規定に該当するもの」とあるのは「沖縄振興開発金融公庫から貸付けを受けた者で産業労働者住宅資金融通法第七条第一項第四号\nの規定に該当するもの」と、「自ら居住するため住宅を必要とする者又は親族の居住の用に供するため自ら居住する住宅以外に住宅を必要とする者」とあるのは「産業労働者住宅資金融通法第二条第一号\nに規定する事業者でその事業に使用する産業労働者に貸し付け、又は譲渡するため住宅を必要とするもの」と、同条第二項第三号\n中「居住し、又は勤務する場所」とあるのは「住所又は事業場」と、第二十九条第一項中「法第三十五条の二第二項」とあるのは「産業労働者住宅資金融通法第十三条の三第二項\n」と読み替えるものとする。",
"enum": {
}
},
"3(2)": {
"main": "譲渡人は、前項において準用する沖縄振興開発金融公庫法施行規則第二十二条第一項\n又は第二十四条第三項\nの規定により譲受人を選定しようとする場合においては、沖縄労働局長の意見を参酌しなければならない。",
"enum": {
}
}
},
"title": "沖縄振興開発金融公庫による産業労働者住宅資金の融通に関する命令",
"cont": {
}
} |
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"id": 1,
"title": "Польза витаминов и минералов",
"subtitle": "Несмотря на то, что все мы знаем о неоспоримой пользе витаминов и минералов, не все из нас знают, в чём...",
"text": "Для того, чтобы дети гармонично развивались и росли, взрослые всегда были в тонусе, а более старшее поколение чувствовало себя в норме, организму необходимы БАДы для всей семьи. Любая женщина мечтает всегда оставаться молодой и красивой, а мужчины хотят быть в тонусе и сохранять свою сексуальную активность как можно дольше. И это лишь «вершина айсберга». Как учесть интересы каждого? Бады Вижион для всей семьи сумели позаботиться о потребности каждого, они гармонично сочетают в себе витамины для любого возраста и пола. <br/>Концепция комплекса Family Hit направлена на удовлетворение суточной необходимости в витаминах и микроэлементах каждого члена семьи. Прием БАДов Вижион для всей семьи полезен для здоровья людей любого возраста и пола вне зависимости от их рода деятельности, уровня физической активности и состояния здоровья. Биодобавки содержат уникальные продукты, предназначенные для улучшения состояния здоровья, повышения иммунитета, продления молодости и не только. В состав витаминов Family Hit входят полифенолы, бета-каротин, аминокислоты, гингко двудольное, витамин Е, а также полиненасыщенные жирные кислоты омега-3. И это далеко не полный их состав. Особо хотелось бы выделить БАД омега 3. Он содержится далеко не во всех витаминных комплексах, но его значение для организма человека между тем огромно.",
"date": "2020-05-09",
"img_path": "img/publications/publication-img-1.jpg"
},
{
"id": 2,
"title": "Фрукты или свежевыжатые соки",
"subtitle": "Давайте же разберемся, что полезнее всего - съесть фрукты или ягоды свежими, выжать из них сок или приг...",
"text": "Для того, чтобы дети гармонично развивались и росли, взрослые всегда были в тонусе, а более старшее поколение чувствовало себя в норме, организму необходимы БАДы для всей семьи. Любая женщина мечтает всегда оставаться молодой и красивой, а мужчины хотят быть в тонусе и сохранять свою сексуальную активность как можно дольше. И это лишь «вершина айсберга». Как учесть интересы каждого? Бады Вижион для всей семьи сумели позаботиться о потребности каждого, они гармонично сочетают в себе витамины для любого возраста и пола. <br/>Концепция комплекса Family Hit направлена на удовлетворение суточной необходимости в витаминах и микроэлементах каждого члена семьи. Прием БАДов Вижион для всей семьи полезен для здоровья людей любого возраста и пола вне зависимости от их рода деятельности, уровня физической активности и состояния здоровья. Биодобавки содержат уникальные продукты, предназначенные для улучшения состояния здоровья, повышения иммунитета, продления молодости и не только. В состав витаминов Family Hit входят полифенолы, бета-каротин, аминокислоты, гингко двудольное, витамин Е, а также полиненасыщенные жирные кислоты омега-3. И это далеко не полный их состав. Особо хотелось бы выделить БАД омега 3. Он содержится далеко не во всех витаминных комплексах, но его значение для организма человека между тем огромно.",
"date": "2020-05-12",
"img_path": "img/publications/publication-img-2.jpg"
},
{
"id": 3,
"title": "БАД для всей семьи для каждого возраста",
"subtitle": "Дело в том, что у каждого возраста и пола свои потребности. Для детей очень важны витамины для роста и м...",
"text": "Для того, чтобы дети гармонично развивались и росли, взрослые всегда были в тонусе, а более старшее поколение чувствовало себя в норме, организму необходимы БАДы для всей семьи. Любая женщина мечтает всегда оставаться молодой и красивой, а мужчины хотят быть в тонусе и сохранять свою сексуальную активность как можно дольше. И это лишь «вершина айсберга». Как учесть интересы каждого? Бады Вижион для всей семьи сумели позаботиться о потребности каждого, они гармонично сочетают в себе витамины для любого возраста и пола. <br/>Концепция комплекса Family Hit направлена на удовлетворение суточной необходимости в витаминах и микроэлементах каждого члена семьи. Прием БАДов Вижион для всей семьи полезен для здоровья людей любого возраста и пола вне зависимости от их рода деятельности, уровня физической активности и состояния здоровья. Биодобавки содержат уникальные продукты, предназначенные для улучшения состояния здоровья, повышения иммунитета, продления молодости и не только. В состав витаминов Family Hit входят полифенолы, бета-каротин, аминокислоты, гингко двудольное, витамин Е, а также полиненасыщенные жирные кислоты омега-3. И это далеко не полный их состав. Особо хотелось бы выделить БАД омега 3. Он содержится далеко не во всех витаминных комплексах, но его значение для организма человека между тем огромно.",
"date": "2020-05-16",
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{"poster":"Nutria Deliciosa","date":"2015-09-26T01:31:51.902+0000","title":"El lag esta en niveles satánicos","subforum":"Problemas Técnicos","up_votes":7,"down_votes":2,"body":"Si yo tengo ping que tengo buena conexión no me quiero imaginar el resto. 124 de ping, ni con Udyr puedo jugar. ¿Si hacemos vaquita entre todos y le compramos un server a riot?","replies":[{"poster":"OtakuSpirit97","date":"2015-09-26T15:01:50.740+0000","up_votes":1,"down_votes":1,"body":"Con ese Ping no se puede jugar ni con Yi, pero poniendolo de tal forma, Riot tiene que compartir los megas de su server a mas de 1 millon de personas, te imaginas un modem usandolo 1 millon de personas al mismo tiempo? {{item:3151}} \nAunque nadie sabe la capacidad de las ''super computadoras'' de Rito,pero tambien estoy de acuerdo en que el ping es altisimo, aunque tarde o temprano el problema se soluciona. lo unico frustrante es que jugas una hora, y tenes 9 horas de ping altisimo..\nParece que los de Riot no ven el problema {{champion:64}}","replies":[]}]} |
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{"response": {"status": "ok", "userTier": "developer", "total": 1, "content": {"id": "tv-and-radio/2014/dec/11/serial-nears-end-reddit-detectives-keep-working", "type": "article", "sectionId": "tv-and-radio", "sectionName": "Television & radio", "webPublicationDate": "2014-12-11T22:29:52Z", "webTitle": "Serial nears its end, but the Reddit detectives keep working", "webUrl": "https://www.theguardian.com/tv-and-radio/2014/dec/11/serial-nears-end-reddit-detectives-keep-working", "apiUrl": "https://content.guardianapis.com/tv-and-radio/2014/dec/11/serial-nears-end-reddit-detectives-keep-working", "fields": {"headline": "Serial nears its end, but the Reddit detectives keep working", "bodyText": "\u201cI was just curious like everybody else \u2026 I just figured out where he lives and found out it wasn\u2019t far,\u201d a Reddit user messaged me late last month. The \u201che\u201d the user was describing was Jay, the prosecution\u2019s main witness in the 1999 murder of Hae Min Lee. That\u2019s the Baltimore case which Serial, the viral podcast from the producers of This American Life, has been reinvestigating for the last two months. It has garnered the rapt attention of over 5 million downloaders. And it will all end next week. A second season will deal with a different case. Jay has not participated in the podcast. This has succeeded only in making him a more interesting target to wannabe detectives. Exhibit A: this user had written on the Reddit that he had driven by Jay\u2019s house and seen him. Perhaps the Redditor was lying, I thought to myself, but I had to ask: Did he have any qualms about doing that, as a relative stranger to the case? \u201cNo, not really,\u201d he replied. \u201cI had no plans of making contact or sitting outside and waiting.\u201d He simply wanted to see the house, and Jay. Creepy, right? Yet a couple of weeks after trading these messages, I listened to an episode where Sarah Koenig, the show\u2019s host, told a similar story. Needing some answers, she drove straight up to Jay\u2019s house with no warning. This, she admitted, was a \u201cdick move\u201d. Koenig actually knocked on the door. Inside, she and a producer spoke to Jay without recording the conversation. And when they got back to the car they proceeded to narrate the encounter back to us, without quite saying if Jay approved. We only know that he subsequently declined an interview. In other words, there are moments where the line between the journalist and the Redditor is not as clear as we would like. Since I last wrote about it for the Guardian, the plot in Serial, as described by Koenig, has certainly thickened. But then, so has everything else: the audience, the criticism and the backlash to the criticism. Most of all, the online discussion by amateur detectives has blossomed further. The subreddit devoted to the podcast now draws more than 700,000 unique views a month. The general outlines of the crime, however, haven\u2019t changed much since the first episode. On 13 January 1999, someone strangled Lee. Her body was only found much later, buried in a park. Jay told the police that Adnan Syed, Lee\u2019s ex-boyfriend, was the killer. Two trials, a fairly thin evidentiary record, one plea deal for Jay, and an uneven defense lawyer followed. Ultimately, Syed was convicted. He maintains his innocence. He\u2019s been in prison since his conviction. Enter Serial, and Koenig. Her exploration of the case has proven addictive. But the serialised approach has invited people, in a way it has never been clear Serial\u2019s producers anticipated, to Monday-morning-quarterback the investigation. The resulting online discussions have been fractious and occasionally taken, in the way of the internet, a turn for the insane. The show has ignored those discussions, even where it seems like they might be relevant. Today\u2019s episode, for example, was titled Rumours. And it addressed some stories that had been floating around Reddit for weeks, without ever mentioning Reddit itself. (I contacted Serial\u2019s producers for comment on Reddit\u2019s relationship to their reporting, but they declined.) It\u2019s easy to dismiss all this as \u201cjust Reddit,\u201d because so much of what\u2019s gone on there has really been about the obsessive armchair-detective types. And yet something else has happened too: the people who are actually involved in the case have used the internet to push back. The starkest example of that came when Lee\u2019s brother, whom Serial producers had evidently not been able to reach, wrote a post on the subreddit on 18 November. He titled it, \u201cI am Hae\u2019s brother - Do not AMA [Ask Me Anything]\u201d. In it he told the redditors that they were \u201cdisgusting,\u201d that \u201cTO ME ITS REAL LIFE.\u201d He seemed less bothered by the podcast than the online discussions themselves. The redditors, generally, seemed chastened. \u201cI am very sorry for your loss,\u201d begins the top comment. (A Reddit moderator, Jacob White, told me then that they are not 100% certain that this poster was actually Hae\u2019s brother. But, he added, \u201cFor our subreddit\u2019s uses however, I have confidence enough for the users to carry on conversation. If that makes sense.\u201d) Another person who surfaced on Reddit about two weeks ago is Tanveer Syed, 38. He\u2019s Adnan\u2019s older brother, and I spoke with him by phone. His first subreddit intervention came because several of the redditors had seized on a \u201cfact\u201d about Tanveer himself. Someone in the defense lawyer\u2019s office had written a note in the file saying Tanveer had called Adnan a \u201cmasterful liar.\u201d Tanveer denies this. He says the law clerk misconstrued his stories about Adnan, that he\u2019d only said Adnan told ordinary teenager\u2019s lies about where he was going out to at night. Specifically, Tanveer says, he\u2019d never have used the phrase \u201cmasterful liar,\u201d because to him it\u2019s \u201cawkward language.\u201d But that phrase kept surfacing on the Reddit, he and his wife noticed. And after several weeks of this, they\u2019d had enough. One night, he was \u201cputting my 10-month-old to sleep, and my wife came in and was like: \u2018They\u2019re talking about the masterful liar thing again!\u2019\u201d And so he went online to correct them. Since then Tanveer has intervened several times on the subreddit. I asked him about the emotional toll I assumed this must take on him, but Tanveer was sanguine. It didn\u2019t bother him as much as it bothered his younger brother Yusuf, he said. (Yusuf recently told the Guardian\u2019s Jon Ronson that he\u2019d found Reddit \u201ctoxic,\u201d though he also had trouble looking away from it.) \u201cI had 21 years of my life before it got ruined by Adnan getting arrested,\u201d Tanveer said. But his youngest brother had been in second grade. Tanveer attended the trial; he was used to people attacking his brother\u2019s credibility. Yusuf, meanwhile, who\u2019d been so young, was \u201cseeing all this stuff, like most people, for the first time\u201d. Recently Tanveer actually found himself on the phone with Adnan, trying to explain the online furor over Serial. Adnan has no experience of social media, he says, so Tanveer had to find another metaphor to explain things. \u201cReddit is like road rage,\u201d he says he told Adnan. People were very reactive and emotional. And under cover of anonymity, lots felt free to say things they would never say to Adnan\u2019s face. \u201cFor Adnan, it was hard to fathom because Adnan\u2019s been in jail,\u201d Tanveer said. \u201cAdnan said: \u2018In my world, if you\u2019re not ready to say something to someone\u2019s face, you don\u2019t say it.\u2019\u201d Tanveer and Adnan are not alone in seizing on the frustrating anonymity of these people on the internet. In the last week, I also spoke to Rabia Chaudry, the family friend who alerted Koenig to the case, about her involvement with Reddit. Early on, she was an active user. But a few weeks ago, she publicly declared she\u2019d deleted her Reddit account. At the time, as a regular lurker on the subreddit, I could completely see why. After the first few weeks, other users had begun to describe Rabia in terms more appropriate to a cartoon villainess. People resented her unqualified advocacy of Adnan\u2019s innocence, and their resentment inflated her into a character for them to bat around in their discussions. Family and friends still send her screenshots, sometimes. \u201cAnd it\u2019s hard, sometimes there are these really, deeply personal attacks,\u201d she said. \u201cMe and Adnan\u2019s family, you know, his loved ones, might take things personally\u2026 But why are strangers taking things so personally? I don\u2019t get it. It\u2019s so toxic.\u201d Both Tanveer and Rabia did have some theories as to why some users were so invested. They suggested that some anonymous users may be close to the case, though they\u2019re not admitting it. They couldn\u2019t prove anyone\u2019s identity, though. In fact, it\u2019s hard to definitively prove that anyone is on Reddit unless they voluntarily submit to verification. We only know, for example, that the person claiming to be Hae\u2019s brother who posted on Reddit was that person through the confirmation the moderators sought. The rumour that Jay himself was on the reddit, reported last week by Ronson \u2013 well, the moderators deny it. And even Tanveer told me he thought that was a misunderstanding. As for myself, after weeks of these meta-conversations, I don\u2019t know that any of the online obsessiveness about Serial has a clear explanation. The phrase I keep coming back to, instead, is the one with which this article opens: \u201cI was just curious like everybody else.\u201d I\u2019d never have driven up to Jay\u2019s house unannounced, not even as a reporter with several months of work under my belt like Koenig. But I can understand the pull. Investigative reporting, like storytelling, or like listening to stories, can become its own kind of hypnosis. Because I can\u2019t discuss these issues with Koenig herself, I emailed Pamela Colloff for some insight. Colloff is an award-winning reporter for the Texas Monthly, where she has written long investigative crime pieces for years. I asked her whether she\u2019d ever consider opening up her reporting to a serialised format the way Koenig has. She replied that though she\u2019d been enjoying listening to Serial, she wouldn\u2019t present a story this way herself. \u201cDoing so would create an ethical minefield, at least for me,\u201d Colloff wrote. \u201cGood crime writing requires suspense, but stretching that out over a protracted period of time can be problematic. Is it OK for us to wonder for two or three months what the deal is with Jay, to borrow a phrase from the podcast? Or should we be presented with all relevant information about Jay at one time?\u201d In part that\u2019s because there is an additional ethical burden associated with crime reporting: \u201cThe evidence you uncover, and the way you frame the story, can have tremendous influence on the case itself.\u201d The participants in this case do feel that influence, by the way. When I spoke to Rabia this past weekend, she was very concerned that the latest Serial episode, about Adnan\u2019s defense lawyer, might affect his future appeals. They\u2019re based in a theory known as \u201cineffective assistance of counsel.\u201d Koenig had presented Adnan as having had more or less total faith in his defence attorney at the time of the trial. But Rabia had spoken to Adnan since and she said he was upset. Adnan, Rabia says, had told Koenig that his confidence in the attorney had since been undermined by what he\u2019d learned after the trail. But Koenig hadn\u2019t aired that part of the interview. \u201cHe was hurt by it,\u201d Rabia said. \u201cThe fact that he told Sarah the whole thing, and it wasn\u2019t reported like that, bothered him. And it bothered me.\u201d She says she spoke to Koenig about it. Rabia also says she does not think Koenig intended to harm Adnan\u2019s defense in any way. At the end of today\u2019s episode, Koenig seemed to me to be addressing this. She talked about a letter from Adnan, dated \u201ca few weeks ago,\u201d in which he tried to explain some things about his relationship to her. \u201cAdnan is obviously aware of this podcast, that it\u2019s out in the world and I could tell that my story had messed with his equilibrium,\u201d she said. 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{"poster":"M00NSCream","date":"2015-03-29T16:45:33.805+0000","title":"Problemi di connessione","subforum":"Aiuto e supporto","up_votes":1,"down_votes":0,"body":"Salve ragazzi!questo è il mio primo post. Oggi per colpa della mia connessione ho mollato ben 2 partite. Solita roba....gioco tranquilllamente e poi mi crasha la connessione.10 minuti per riconnettermi e BAM! un bel messaggio dal leaverbuster perchè dice che ero afk. Sinceramente mi sono rotto di vedere la gente che continua a scrivere report anche per soli 5 minuti di connessione persa pur spiegandogli il tuo problema. Volevo chiedere se c'è un modo che impedisca questi ban inutili solo per colpa della connessione che crasha.","replies":[{"poster":"Phanix","date":"2015-03-30T08:24:26.731+0000","up_votes":1,"down_votes":0,"body":"se ti appare il messaggio ma sei entrato non pigiare ok ma abbassalo fino a farlo scomparire e gioca XD","replies":[]},{"poster":"Whommy","date":"2015-03-30T07:25:59.095+0000","up_votes":1,"down_votes":0,"body":"Quello è un messaggio automatico del leaverbuster non dei report, sicuramente ti sarai preso anche i report.\n\nSi attiva dopo 4-5 min di afk in ogni caso sia che ti cada la linea sia se esci volontariamente o anche se gironzoli per la fontana.\n\nIl ban è fatto apposta per queste situazioni, per gli afk intenzionali e per chi ha problemi di connessione, in ogni caso rovini la partita degli altri.\nIl sistema non è in grado di distinguere un crash della linea da un abbandono intenzionale.\n\nRisolvi i tuoi problemi di connessione poi gioca, vedrai che il ban non lo prendi.","replies":[]}]} |
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{
"directions": [
"Cook sugar and orange juice in heavy medium saucepan over low heat, stirring until sugar dissolves. Increase heat and boil without stirring until syrup turns deep golden brown, brushing down sides of pan with wet pastry brush and swirling pan occasionally, about 15 minutes; mixture will be foamy. Add cream and butter (mixture will bubble) and whisk until smooth. Whisk over medium heat until mixture thickens slightly and is deep caramel color, about 2 minutes. Remove from heat. Whisk in sour cream. Stir in pine nuts. Let cool 5 minutes. Mix in orange peel. Cool until just warm. (Can be prepared 3 days ahead. Cover and refrigerate. Rewarm over low heat before serving.)"
],
"ingredients": [
"2 cups sugar",
"1/2 cup orange juice",
"1/2 cup whipping cream",
"3 tablespoons butter",
"2/3 cup sour cream",
"2/3 cup toasted pine nuts",
"1 tablespoon finely minced orange peel (orange part only)"
],
"language": "en-US",
"source": "www.epicurious.com",
"tags": [
"Sauce",
"Milk/Cream",
"Nut",
"Orange",
"Pine Nut"
],
"title": "Pine Nut-Orange Caramel Sauce",
"url": "http://www.epicurious.com/recipes/food/views/pine-nut-orange-caramel-sauce-2837"
}
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{
"directions": [
"Preheat oven to 275 degrees F (135 degrees C). Line 2 baking sheets with parchment paper.",
"Combine brown sugar, water, and honey in a large microwave-safe bowl. Microwave on high until sugar is completely dissolved, about 5 minutes. Stir in coconut oil, vanilla, and salt.",
"Mix rolled oats, quick-cooking oats, almonds, puffed quinoa, chia seeds, and shredded coconut together in a large bowl. Pour in sugar mixture and mix thoroughly until granola is combined and starting to clump together.",
"Spread granola mixture no more than 3/4-inch high on prepared baking sheets.",
"Bake in the preheated oven until golden and crunchy, 35 to 45 minutes. Allow to cool completely."
],
"ingredients": [
"1 1/2 cups brown sugar",
"1/2 cup water",
"1/4 cup honey",
"1/4 cup coconut oil",
"1 tablespoon vanilla extract",
"salt to taste",
"3 cups rolled oats",
"3 cups quick-cooking oats",
"2 cups chopped almonds",
"1 1/2 cups puffed quinoa",
"1/4 cup chia seeds",
"1/4 cup shredded coconut"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Perfectly Crunchy Granola",
"url": "http://allrecipes.com/recipe/246773/perfectly-crunchy-granola/"
}
|
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{"poster":"Kleriker85HH","date":"2015-06-21T17:27:42.100+0000","title":"Platin Team sucht Top, Midlane und Support [ Platin 2+] für Neuaufbau","subforum":"Clans & Teams","up_votes":1,"down_votes":1,"body":"Platin5 Team sucht Top, Midlane und Support [ Platin 2+] für Neuaufbau\r\n\r\nWIr sind Teil eines CLan [liQs]\r\n\r\nSuchen sehr sehr aktive und zuverlässige Spieler, wir sind jeden Tag online !\r\n\r\nAdc und Jungler sind beide Platin 2\r\n\r\nIngame: \r\nYukíhira Soma\r\nKleriker85HH","replies":[{"poster":"21 Saltlord","date":"2015-06-21T18:27:42.356+0000","up_votes":1,"down_votes":0,"body":"Kleriker, wie kommts das du net mehr bei PrG bist :O ?","replies":[{"poster":"Kleriker85HH","date":"2015-06-24T17:21:40.847+0000","up_votes":1,"down_votes":0,"body":"vielleicht bin ich es ja noch ;P","replies":[]}]}]} |
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{"poster":"DilanIgnacio","date":"2015-02-11T21:17:26.064+0000","title":"99% QUE HAGO?","subforum":"Charlas Generales","up_votes":1,"down_votes":0,"body":"el lol se me queda a 99% y no se que hacer ¿que puedo hacer? reiniciar el launcher, reinstalarlo o repararlo? porfavor si pueden ayuden GRACIAS","replies":[{"poster":"Yulisitaa","date":"2015-07-22T02:56:36.172+0000","up_votes":1,"down_votes":0,"body":"igual me pasa lo mismo qe ago?","replies":[]},{"poster":"Auritre","date":"2015-02-11T21:55:09.288+0000","up_votes":1,"down_votes":0,"body":"http://boards.las.leagueoflegends.com/es/c/ayuda-y-soporte/6Ug9f2Ov-mantenimiento-programado-actualizacian-53\n\nRiot admite que detectaron problemas...\n\nLa solución cerralo y volvelo a abrir y dejalo escaneando archivos por un par de horas hasta que decida actualizarse...\nOsea, abrilo y andate al parque porque la actualización va a demorar horas....","replies":[]}]} |
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{"category": "Civil Appeal", "status": "Remittitur Issued/Case Closed", "case_url": "http://caseinfo.nvsupremecourt.us/public/caseView.do?csIID=26614", "caption": "WARTENBERG VS. PETRILLO", "type": "General", "case_no": "58464", "subtype": "Other", "parties": [{"Represented By": "Casey J. Quinn (Gordon & Rees, LLP)", "Role": "Appellant", "Party Name": "Alla V. Wartenberg"}, {"Represented By": "Casey J. Quinn (Gordon & Rees, LLP)", "Role": "Appellant", "Party Name": "Daniel J. Wartenberg"}, {"Represented By": "Joseph Timothy Nold (Accelerated Law Group)", "Role": "Respondent", "Party Name": "Janet D. Petrillo"}], "docket": [{"Date": "06/01/2011", "Type/Subtype": "Filing Fee - Filing Fee due", "Description": "Filing fee due for Appeal."}, {"Type/Subtype": "Notice of Appeal Documents - Notice of Appeal", "Description": "Filed Notice of Appeal. 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The requesting of transcripts and briefing shall remain stayed pending further order of this court. Nos. 58051/58464 - not consolidated.", "Document Number": "11-25819", "Document URL": "/document/view.do?csNameID=26614&csIID=26614&deLinkID=346592&sireDocumentNumber=11-25819", "Date": "08/24/2011", "Pending?": "NA"}, {"Type/Subtype": "Notice/Incoming - Status Report", "Description": "Filed Status Report. Nos. 58051/58464 - not consolidated.", "Document Number": "11-27380", "Document URL": "/document/view.do?csNameID=26614&csIID=26614&deLinkID=348228&sireDocumentNumber=11-27380", "Date": "09/08/2011", "Pending?": "NA"}, {"Type/Subtype": "Notice/Incoming - Status Report", "Description": "Filed Response to Petrillo's Status Report. 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{"poster":"OMuMuO","date":"2015-05-13T13:32:47.737+0000","title":"Verbindung zum PvP.net wurde unterbrochen","subforum":"Hilfe & Support","up_votes":1,"down_votes":0,"body":"was ist das problem ??? seit letzten patch bekomme ich immer diese meldung...\r\n\r\nKingBloKK: i pref supp but can all\r\nDeine Verbindung zum PvP.net wurde unterbrochen. Es wird versucht, dein Spiel durch eine erneute Verbindung wiederherzustellen ...\r\nErneute Verbindung mit PvP.net hergestellt.\r\nDeine Verbindung zum PvP.net wurde unterbrochen. Es wird versucht, dein Spiel durch eine erneute Verbindung wiederherzustellen ...\r\n\r\nwas machen???","replies":[{"poster":"echo sunset","date":"2015-05-13T16:35:28.907+0000","up_votes":1,"down_votes":0,"body":"Versuch' das mal:\n\nhttps://www.youtube.com/watch?v=PEm_wvVprZY&feature=youtube_gdata_player","replies":[{"poster":"IWILLFLOORYOU1","date":"2015-08-20T18:28:36.936+0000","up_votes":1,"down_votes":0,"body":"funktioniert danke dir !!","replies":[]},{"poster":"OMuMuO","date":"2015-05-13T17:40:09.478+0000","up_votes":1,"down_votes":0,"body":"Wuhu dank dir :) hat geklappt","replies":[]}]},{"poster":"Enodia","date":"2015-05-14T20:05:32.595+0000","up_votes":1,"down_votes":0,"body":"genau das gleiche ist bei mir auch aber seit dem patch mit der neuen Ashe kann es nicht einmal mehr patchen: \n \n Aktualisierung fehlgeschlagen\n\n\n Ein nicht näher spezifizierter Fehler ist aufgetreten. Bitte\n übermittle die Berichte, damit wir uns darum kümmern können.\n\n\n\n\n\n\n\n\nwo soll ich die Berichte übermitteln (an welche E-mail)?\nbitte um hilfe !!!","replies":[]},{"poster":"Doctor JayDee","date":"2015-05-13T17:30:32.093+0000","up_votes":1,"down_votes":0,"body":"same problem here :(","replies":[]}]} |
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{"poster":"HookMachinê","date":"2018-12-17T17:11:31.208+0000","title":"Mid/Supp main sucht Team (Gold 3)","subforum":"Clans & Teams","up_votes":1,"down_votes":0,"body":"Hallo Leute,\r\n\r\nich bin derzeit Mid und Support main, 21 Jahre alt und spiele seit Season 3.\r\nZu meinen Mains gehören unter anderem Alistar, Lux, Thresh, Leona, Syndra, Kassadin, Nami, LB und viele mehr...\r\n\r\nIch suche ein Team das sehr aktiv ist und auch gerne bei Turnieren mitspielt, ich habe Teamerfahrung und besitze Ts3 und Discord.\r\n\r\nFalls ihr interesse habt könnt ihr mich ingame adden ^^\r\n\r\nMfG ApplePiê","replies":[]} |
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{"poster":"Manwalrus","date":"2015-12-01T15:57:51.150+0000","title":"Don't let last year's allstar champ vote happen again!!!","subforum":"Esports","up_votes":148,"down_votes":10,"body":"Last years champions picks were: \r\nTeam Fire: \r\n{{champion:412}} \r\n{{champion:81}} \r\n{{champion:64}} \r\n{{champion:236}} \r\n{{champion:238}} \r\n\r\nTeam Ice: \r\n{{champion:412}} \r\n{{champion:67}} \r\n{{champion:34}} (this was pretty cool) \r\n{{champion:236}} \r\n{{champion:64}} \r\n\r\nWe have a chance to make the pros play anything we want, let's make the best of it and not pick the same meta cookie cutter champions over and over, let's see some Poppy, Yorick, Heimerdinger, maybe even fiddlesticks (these are just examples) \r\nLet's get the pros to play some different champs this year.","replies":[{"poster":"ProphaneProphet","date":"2015-12-01T17:45:02.450+0000","up_votes":76,"down_votes":0,"body":"I couldn't help but be incredibly corny and choose Fire and Ice themed champs (base skins).\n\n{{summoner:14}} {{champion:102}} {{champion:10}} {{champion:63}} {{champion:1}} {{champion:89}} \n{{summoner:32}} {{champion:48}} {{champion:113}} {{champion:127}} {{champion:22}} {{champion:201}} \n\nYeah they probably aren't ideal teams, but that's not the point here is it?","replies":[{"poster":"Castozor","date":"2015-12-01T18:44:41.561+0000","up_votes":12,"down_votes":1,"body":"Team Ice doesn't even look bad with their CC overload, and swap out Kayle and either Annie/Leona for a proper bot and you're set to go for fire.","replies":[]},{"poster":"Quort","date":"2015-12-02T00:01:52.743+0000","up_votes":8,"down_votes":0,"body":"Why not Phoenix Quinn as ADC? Then you could have Kayle top, Shyvana jungle, Brand mid, Leona support. :3","replies":[]},{"poster":"Jeddy017","date":"2015-12-01T18:44:37.959+0000","up_votes":6,"down_votes":1,"body":"Replace Kayle with Rumble & boom,we would have had matching votes.","replies":[]},{"poster":"T RexHasTinyArms","date":"2015-12-02T06:34:02.263+0000","up_votes":3,"down_votes":0,"body":"Do they still do pros vs casters/rioters? I miss those matches. Pros get the worst comp of all supports that they could come up w/ and the casters get the strongest meta comp they feel like picking, and the pros win any way. Maybe it doesn't work any more w/ all the retired pros casting, but it was funny and really interesting to watch bc it was somewhat balanced but you really saw what could be done by abusing champ/game knowledge rather than having a good match up or strong champ.","replies":[]}]},{"poster":"Linthe","date":"2015-12-01T15:59:20.325+0000","up_votes":5,"down_votes":1,"body":"Pretty dang funny. And I agree. Upvoted.","replies":[{"poster":"Manwalrus","date":"2015-12-01T16:00:55.885+0000","up_votes":51,"down_votes":0,"body":"allow me to quote the top comment from the pick ten results announcement last year:\n\n \"The community fucking sucks at picking champions\"","replies":[{"poster":"warpenguin555","date":"2015-12-01T17:11:10.891+0000","up_votes":1,"down_votes":0,"body":"How many upvotes?","replies":[{"poster":"Manwalrus","date":"2015-12-01T20:22:42.476+0000","up_votes":9,"down_votes":0,"body":"429.","replies":[{"poster":"warpenguin555","date":"2015-12-01T20:24:30.392+0000","up_votes":1,"down_votes":0,"body":"lol thanks. i want the link now lol","replies":[{"poster":"Manwalrus","date":"2015-12-01T20:37:31.050+0000","up_votes":5,"down_votes":0,"body":"http://na.leagueoflegends.com/en/news/esports/esports-event/all-star-pick-10-results-are","replies":[]}]}]}]}]}]},{"poster":"Hangsterr","date":"2015-12-01T16:04:47.181+0000","up_votes":3,"down_votes":27,"body":"I mean clearly your just voting up same champ as last year or most of em\n\nAll those Champ we saw em too much in LCS and World \nbut it whatever get the most Vote in the end\n\nbut I voted\n{{champion:23}} \n{{champion:106}} \n{{champion:238}} \n{{champion:17}} \n{{champion:161}}","replies":[{"poster":"Manwalrus","date":"2015-12-01T16:07:02.524+0000","up_votes":25,"down_votes":0,"body":">I mean clearly your just voting up same champ as last year or most of em\n\nWat? This post is literally about NOT picking the same champs.","replies":[{"poster":"Hangsterr","date":"2015-12-01T16:08:35.821+0000","up_votes":5,"down_votes":14,"body":"Oh well mb LOL\nThought you were voting for those champs","replies":[{"poster":"macromite","date":"2015-12-01T19:44:13.215+0000","up_votes":25,"down_votes":0,"body":"this is what reading skills are for.","replies":[{"poster":"blueberrypancake","date":"2015-12-01T22:38:02.389+0000","up_votes":3,"down_votes":0,"body":"That ia actually mentioned on the boxes for pokemon games","replies":[]}]}]}]}]},{"poster":"warpenguin555","date":"2015-12-01T18:01:23.195+0000","up_votes":16,"down_votes":2,"body":"What I voted(top/jg/mid/adc/sup):\n\nFire:{{champion:83}} {{champion:9}} {{champion:3}} {{champion:21}} {{champion:143}} \nVS\nIce: {{champion:75}} {{champion:33}} {{champion:74}} {{champion:6}} {{champion:44}} \n\nwhats going to happen\nFire:{{champion:114}} {{champion:64}} {{champion:157}} {{champion:429}} {{champion:412}} \nVS\nIce: {{champion:92}} {{champion:64}} {{champion:157}} {{champion:67}} {{champion:412}} \nWITH\nme not watching","replies":[]},{"poster":"Puynsi","date":"2015-12-01T20:08:27.275+0000","up_votes":10,"down_votes":0,"body":"Fire:\n{{champion:39}} {{champion:223}} {{champion:157}} {{champion:67}} {{champion:63}} \nIce:\n{{champion:36}} {{champion:114}} {{champion:18}} {{champion:412}} {{champion:24}} \n\nThe most obnoxious champs vs the most obnoxious champs and watch everyone leave the stream because of the fear of getting cancer.","replies":[{"poster":"warpenguin555","date":"2015-12-01T20:21:26.647+0000","up_votes":6,"down_votes":0,"body":"replace trist with kalista and you got it. also need to replace Illaoi becuase you cant even vote for her. might i suggest fiora or riven?","replies":[{"poster":"Puynsi","date":"2015-12-01T20:44:53.240+0000","up_votes":1,"down_votes":1,"body":"I edited and left Trist in because shes a really obnoxious hyper carry with bs damage that has little counterplay, just like her AP counterpart used to be.\nAlso fiora because muh big riposte plays","replies":[{"poster":"warpenguin555","date":"2015-12-01T20:46:08.041+0000","up_votes":2,"down_votes":0,"body":"true, their trist always has rocket jump, but the ones we get never do XD","replies":[]}]}]}]},{"poster":"kneel on Ice","date":"2015-12-01T22:25:28.180+0000","up_votes":7,"down_votes":0,"body":"Team Ice : {{champion:22}} {{champion:201}} {{champion:127}} {{champion:48}} {{champion:113}} Hands down","replies":[{"poster":"Valenten","date":"2015-12-02T08:56:20.594+0000","up_votes":2,"down_votes":0,"body":"I mean.... {{champion:127}} {{champion:113}} {{champion:34}} {{champion:22}} {{champion:201}} \nis the team that I want for ice.","replies":[]},{"poster":"CarameI Frappe","date":"2015-12-01T23:54:47.781+0000","up_votes":2,"down_votes":0,"body":"Logged in to upvote this. Yes please, this is what I want to see!","replies":[]}]},{"poster":"warpenguin555","date":"2015-12-01T17:09:22.022+0000","up_votes":7,"down_votes":0,"body":"Vote Galio on Faker","replies":[]},{"poster":"Crackers","date":"2015-12-01T17:26:34.379+0000","up_votes":6,"down_votes":0,"body":"While I do tend to agree with this sentiment, I believe it may start a war of votes between the non-meta vs the people that may want to see people like Faker playing their best champion they are famous for. It can also be hard to get people to agree on what champion to even vote for in relation to this unless some giant reddit thread comes up or something basically telling all of League to \"make Faker play Galio\" etc. Votes would not even be consistent. In the end stuff like Thresh may just win regardless for a support. Other votes may get thrown away. It would be like trying to get everyone in this thread to vote for a pizza with the topping they want. I support this, I really do, but I kept my votes to each champion playing their strongest champs they are famous for to see this game played at its highest skill level. I believe it would be hard to convince everyone to put Galios, Yorricks, and Poppy in these kind of games. Plus I fear that overwhelming Teemo vote.\n\nMy Votes as of now:\n**Pick 10**\n{{summoner:14}} - {{champion:68}} {{champion:421}} {{champion:7}} {{champion:42}} {{champion:53}} VS\n{{summoner:32}} - {{champion:57}} {{champion:28}} {{champion:268}} {{champion:67}} {{champion:12}} \n\n**ALL STAR**\n{{summoner:14}} Dyrus, Score, Faker, Doublelift, Madlife\n{{summoner:32}} Huni, Clearlove, Rookie, Uzi, Pyl\n\n**SKIN** \n{{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}}","replies":[{"poster":"BakedLotion","date":"2015-12-01T19:36:57.814+0000","up_votes":3,"down_votes":3,"body":"> [{quoted}](name=Crackers,realm=NA,application-id=9hBQwnEU,discussion-id=XiWaJPzg,comment-id=0006,timestamp=2015-12-01T17:26:34.379+0000)\n>\n> While I do tend to agree with this sentiment, I believe it may start a war of votes between the non-meta vs the people that may want to see people like Faker playing their best champion they are famous for. It can also be hard to get people to agree on what champion to even vote for in relation to this unless some giant reddit thread comes up or something basically telling all of League to \"make Faker play Galio\" etc. Votes would not even be consistent. In the end stuff like Thresh may just win regardless for a support. Other votes may get thrown away. It would be like trying to get everyone in this thread to vote for a pizza with the topping they want. I support this, I really do, but I kept my votes to each champion playing their strongest champs they are famous for to see this game played at its highest skill level. I believe it would be hard to convince everyone to put Galios, Yorricks, and Poppy in these kind of games. Plus I fear that overwhelming Teemo vote.\n> \n> My Votes as of now:\n> **Pick 10**\n> {{summoner:14}} - {{champion:68}} {{champion:421}} {{champion:7}} {{champion:42}} {{champion:53}} VS\n> {{summoner:32}} - {{champion:57}} {{champion:28}} {{champion:268}} {{champion:67}} {{champion:12}} \n> \n> **ALL STAR**\n> {{summoner:14}} Dyrus, Score, Faker, Doublelift, Madlife\n> {{summoner:32}} Huni, Clearlove, Rookie, Uzi, Pyl\n> \n> **SKIN** \n> {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}} {{champion:131}}\n\nso basically you want them to play every champion that's already commonly played. Boy are you fun.","replies":[{"poster":"Spizzle9000","date":"2015-12-01T22:45:09.074+0000","up_votes":2,"down_votes":0,"body":"I don't really ever see (at least in my matches) any of them except Vayne and Blitzcrank frequently. I see Rumble like twice a month, haven't played with or against Rek'Sai for 2 months, LeBlanc was three weeks ago, Corki was two weeks ago, and Maokai was a month ago.\n\nEvelynn, Azir, and Alistair or kinda common-ish? but I really only see Vayne and Blitz out of those 10 often.\n\nPersonally I'd like to see some {{champion:8}} or {{champion:127}} action.","replies":[]}]}]},{"poster":"brad","date":"2015-12-01T21:23:15.304+0000","up_votes":1,"down_votes":7,"body":"how about u let people pick what they want to see","replies":[{"poster":"Manwalrus","date":"2015-12-01T22:09:31.810+0000","up_votes":9,"down_votes":1,"body":"I'm not \"forcing\" anyone to do what I want, I'm saying that it would be a disappointment if we have to see the same old champions again and again, but hey man, if you want to see {{champion:114}} {{champion:64}} {{champion:157}} {{champion:67}} and {{champion:412}} vs {{champion:114}} {{champion:64}} {{champion:157}} {{champion:67}} and {{champion:412}} again then go for it dude.","replies":[]}]},{"poster":"cloman100","date":"2015-12-02T02:43:45.025+0000","up_votes":5,"down_votes":0,"body":"My Picks Are The Same For Both Teams...\n{{champion:238}} {{champion:203}} {{champion:432}} {{champion:78}} {{champion:35}} \nGG","replies":[]},{"poster":"Rigbum","date":"2015-12-01T17:52:00.704+0000","up_votes":5,"down_votes":0,"body":"Where do we vote for this? I haven't seen anything about a vote yet.","replies":[]},{"poster":"Laughing Fish","date":"2015-12-02T14:29:07.978+0000","up_votes":6,"down_votes":1,"body":"I chose\nTeam {{summoner:14}}: {{champion:1}} {{champion:63}} {{champion:102}} {{champion:104}} {{champion:41}} \nTeam {{item:3110}}: {{champion:34}} {{champion:22}} {{champion:113}} {{champion:48}} {{champion:201}} \nAnd {{champion:131}} as the skin choice.","replies":[]},{"poster":"Boomerangbro","date":"2015-12-02T05:40:48.564+0000","up_votes":4,"down_votes":0,"body":"Can I PLEASE see how {{champion:3}} is played at a professional level!!!??","replies":[]},{"poster":"MaximumNinja17","date":"2015-12-02T05:22:17.844+0000","up_votes":4,"down_votes":0,"body":"I voted \n{{champion:44}} {{champion:432}} {{champion:83}} {{champion:20}} {{champion:33}} \nfor both teams. \nCrosses fingers for faker on yorick or taric","replies":[]},{"poster":"RP Sugar Daddy","date":"2015-12-02T05:25:37.051+0000","up_votes":5,"down_votes":1,"body":"Fire\n{{champion:1}} \n{{champion:119}} \n{{champion:63}} \n{{champion:150}} \n{{champion:102}} \n\nIce\n{{champion:201}} \n{{champion:22}} \n{{champion:34}} \n{{champion:113}} \n{{champion:106}}","replies":[]},{"poster":"The0neBarWarrior","date":"2015-12-01T20:10:01.671+0000","up_votes":2,"down_votes":0,"body":"Nah lets vote yasuo in..... and then conversely vote malzahar in as well. That will be fun.","replies":[{"poster":"warpenguin555","date":"2015-12-01T20:17:09.024+0000","up_votes":5,"down_votes":1,"body":"Riot will gut malz for it. not like they dont want to do it already though","replies":[]}]},{"poster":"Regu1us 9","date":"2015-12-02T01:13:02.635+0000","up_votes":3,"down_votes":0,"body":"{{summoner:14}} {{summoner:32}} \n{{champion:89}} {{champion:3}} \n{{champion:268}} {{champion:31}} \n{{champion:57}} {{champion:20}} \n{{champion:412}} {{champion:80}} \n{{champion:126}} {{champion:62}} \n\n10/10 would watch","replies":[]},{"poster":"alfavhunter","date":"2015-12-02T01:04:39.546+0000","up_votes":3,"down_votes":0,"body":"Adc anivia\nSupport gnar\nMid alistar\nJungle blitz\nTop urgot","replies":[]},{"poster":"Smart Kitty","date":"2015-12-02T00:16:58.060+0000","up_votes":3,"down_votes":0,"body":"I was just going to make a post about this as soon as I saw voting up. Though to be fair, they only picked vayne cuz they wanted double on vayne, not so much for the meta. Anivia for froggen obviously as well. Please guys don't vote for leblanc on faker, vote for something uncommon. I'm voting for Swain and Singed for sure, I'll post when I decide on the rest.","replies":[{"poster":"Manwalrus","date":"2015-12-02T00:33:19.117+0000","up_votes":2,"down_votes":0,"body":"I really want to see Faker play {{champion:3}}","replies":[{"poster":"Smart Kitty","date":"2015-12-02T00:52:44.629+0000","up_votes":2,"down_votes":0,"body":"> [{quoted}](name=Manwalrus,realm=NA,application-id=9hBQwnEU,discussion-id=XiWaJPzg,comment-id=00230000,timestamp=2015-12-02T00:33:19.117+0000)\n>\n> I really want to see Faker play {{champion:3}}\n\nI wanna see someone play swain, my main, biased ofc. Since there are actually really good midlaners at allstars, might finally get to see him played well. The only time I've seen Swain win is when Soaz picked him. He's been rekt every other time he's appeared on the rift.","replies":[]}]}]},{"poster":"Chrige","date":"2015-12-01T22:20:02.930+0000","up_votes":2,"down_votes":1,"body":"\"Champ with the most votes will get a fire or ice themed skin.\"\nSatan Teemo skin inbound","replies":[{"poster":"Spizzle9000","date":"2015-12-01T22:49:35.753+0000","up_votes":3,"down_votes":0,"body":"I see it happening, but personally I'd love to see a fire or ice skin for Diana. Plus Teemo has a lot of skins and Diana is I think the oldest champion to have 2 skins. Hell, Gnar will soon have his THIRD skin and he's been out a year. Ekko got his second less than half a year after his release. Bard is getting his second in a couple weeks. I just really want that Diana skin.","replies":[{"poster":"Neamean","date":"2015-12-02T00:34:14.708+0000","up_votes":1,"down_votes":0,"body":"No one remember {{champion:83}}","replies":[{"poster":"Spizzle9000","date":"2015-12-02T00:58:03.810+0000","up_votes":2,"down_votes":0,"body":"Good point. But he hasn't gotten a new skin because almost no one plays him and Riot has ironically basically buried the gravedigger.","replies":[{"poster":"Neamean","date":"2015-12-02T00:59:58.787+0000","up_votes":2,"down_votes":0,"body":"It's not because no one play him it's because he needs a rework or so I've heard.","replies":[{"poster":"Onegarion","date":"2015-12-02T04:59:07.123+0000","up_votes":2,"down_votes":0,"body":"his model also isn't the nicest to make a skin for right now. Not too much to really work with on a champ that is barely played, has a somewhat bad model and is probably slated for a rework","replies":[]}]}]}]}]}]},{"poster":"ShadowDragonAxe","date":"2015-12-02T18:32:14.035+0000","up_votes":2,"down_votes":0,"body":"team fire:\n{{champion:420}} {{champion:203}} {{champion:90}} {{champion:111}} {{champion:254}} \n\nteam ice:\n{{champion:58}} {{champion:3}} {{champion:154}} {{champion:119}} {{champion:143}}","replies":[]}]} |
{"across": {"1": {"clue": "Yawn", "answer": "GAPE", "row": 0, "col": 0}, "5": {"clue": "Murrow's \"Hear ___,\" on radio", "answer": "ITNOW", "row": 0, "col": 5}, "10": {"clue": "Corn or oat follower", "answer": "MEAL", "row": 0, "col": 11}, "14": {"clue": "Like the Gobi", "answer": "ARID", "row": 1, "col": 0}, "15": {"clue": "Stiller's partner", "answer": "MEARA", "row": 1, "col": 5}, "16": {"clue": "Kind of brat or ant", "answer": "ARMY", "row": 1, "col": 11}, "17": {"clue": "Gaspar et al.", "answer": "MAGI", "row": 2, "col": 0}, "18": {"clue": "Phony strong man", "answer": "PAPERTIGER", "row": 2, "col": 5}, "20": {"clue": "Opening", "answer": "SLIT", "row": 3, "col": 0}, "21": {"clue": "Chemical suffix", "answer": "OSE", "row": 3, "col": 5}, "22": {"clue": "Singer Vic", "answer": "DAMONE", "row": 3, "col": 9}, "23": {"clue": "Snare", "answer": "NOOSE", "row": 4, "col": 2}, "25": {"clue": "Part of a NASA vehicle", "answer": "LEM", "row": 4, "col": 8}, "26": {"clue": "Agri Dagi, Mountain of Pain", "answer": "ARARAT", "row": 5, "col": 0}, "28": {"clue": "Meanings", "answer": "PURPORTS", "row": 5, "col": 7}, "33": {"clue": "Cravat material", "answer": "REP", "row": 6, "col": 0}, "34": {"clue": "___ acid (a vitamin)", "answer": "FOLIC", "row": 6, "col": 4}, "36": {"clue": "Ward off", "answer": "AVERT", "row": 6, "col": 10}, "37": {"clue": "Gomberg's instrument", "answer": "OBOE", "row": 7, "col": 0}, "39": {"clue": "Having secret import", "answer": "RUNIC", "row": 7, "col": 5}, "41": {"clue": "Cartoon light bulb", "answer": "IDEA", "row": 7, "col": 11}, "42": {"clue": "Forms", "answer": "MAKES", "row": 8, "col": 0}, "44": {"clue": "Wine region of France", "answer": "MEDOC", "row": 8, "col": 6}, "46": {"clue": "\"Leave ___ to Heaven\"", "answer": "HER", "row": 8, "col": 12}, "47": {"clue": "Departments", "answer": "AGENCIES", "row": 9, "col": 0}, "49": {"clue": "Demure", "answer": "MODEST", "row": 9, "col": 9}, "51": {"clue": "Adviser Landers", "answer": "ANN", "row": 10, "col": 4}, "52": {"clue": "Political slander", "answer": "SMEAR", "row": 10, "col": 8}, "53": {"clue": "Parts of calyces", "answer": "SEPALS", "row": 11, "col": 0}, "57": {"clue": "\"Horton Hears a ___\": Seuss", "answer": "WHO", "row": 11, "col": 7}, "58": {"clue": "Place for a figurehead", "answer": "PROW", "row": 11, "col": 11}, "61": {"clue": "Trapshooter's target", "answer": "CLAYPIGEON", "row": 12, "col": 0}, "63": {"clue": "Arizona Indian", "answer": "PIMA", "row": 12, "col": 11}, "64": {"clue": "Hero of 2,327 performances", "answer": "ABIE", "row": 13, "col": 0}, "65": {"clue": "Dig", "answer": "DELVE", "row": 13, "col": 5}, "66": {"clue": "Author Bagnold", "answer": "ENID", "row": 13, "col": 11}, "67": {"clue": "Nerio's husband", "answer": "MARS", "row": 14, "col": 0}, "68": {"clue": "Church officer", "answer": "ELDER", "row": 14, "col": 5}, "69": {"clue": "Cols.'s commands", "answer": "RGTS", "row": 14, "col": 11}}, "down": {"1": {"clue": "Seamen's chats", "answer": "GAMS", "row": 0, "col": 0}, "2": {"clue": "U.S.S.R.'s ___ Sea", "answer": "ARAL", "row": 0, "col": 1}, "3": {"clue": "\"Caveat emptor\" item", "answer": "PIGINAPOKE", "row": 0, "col": 2}, "4": {"clue": "Harold Ross, e.g.", "answer": "EDITOR", "row": 0, "col": 3}, "5": {"clue": "Pretender", "answer": "IMPOSTOR", "row": 0, "col": 5}, "6": {"clue": "Irritate", "answer": "TEASE", "row": 0, "col": 6}, "7": {"clue": "Neck portion", "answer": "NAPE", "row": 0, "col": 7}, "8": {"clue": "Lode load", "answer": "ORE", "row": 0, "col": 8}, "9": {"clue": "Guard", "answer": "WARDER", "row": 0, "col": 9}, "10": {"clue": "Disfigure", "answer": "MAIM", "row": 0, "col": 11}, "11": {"clue": "Therefore", "answer": "ERGO", "row": 0, "col": 12}, "12": {"clue": "So be it", "answer": "AMEN", "row": 0, "col": 13}, "13": {"clue": "Ancient Greek instrument", "answer": "LYRE", "row": 0, "col": 14}, "19": {"clue": "Neighbor of St. Petersburg", "answer": "TAMPA", "row": 2, "col": 10}, "24": {"clue": "Clod", "answer": "OAF", "row": 4, "col": 4}, "25": {"clue": "Clear", "answer": "LUCID", "row": 4, "col": 8}, "26": {"clue": "Bouquet", "answer": "AROMA", "row": 5, "col": 0}, "27": {"clue": "Snare again", "answer": "REBAG", "row": 5, "col": 1}, "28": {"clue": "Turpentine sources", "answer": "PINES", "row": 5, "col": 7}, "29": {"clue": "Egg: Comb. form", "answer": "OVI", "row": 5, "col": 11}, "30": {"clue": "Diversion; 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{
"directions": [
"Heat chicken stock in separate pan.",
"In large 4 quart pot, heat olive oil on medium heat. Saute shallots and prosciutto for 3 minutes. Add garlic; saute for 2 minutes.",
"Turn up heat to Medium-High. Add rice and lemon zest, cook 2 to 3 minutes, stirring constantly. Add lemon juice and wine until reduced.",
"Add one 8-oz. ladle chicken stock to rice until absorbed. Keep the rice at just a simmer; continue process for 10 to 15 minutes. Add shrimp before last ladle of stock.",
"Add butter and Romano cheese, stir in well. Place in serving bowl and top with fresh arugula and parsley."
],
"ingredients": [
"1 quart hot chicken stock",
"2 tablespoons olive oil",
"3 tablespoons chopped shallots or red onion",
"8 ounces sliced and julienned Margherita\u00ae prosciutto",
"2 cloves garlic, chopped",
"16 ounces Arborio rice",
"1 lemon, zested and juiced",
"1 cup dry white wine, such as Pinot Grigio",
"1 pound (26 to 30 count) raw shrimp, peeled and deveined",
"6 tablespoons butter",
"4 ounces freshly grated Romano cheese",
"Fresh arugula for garnish",
"1 tablespoon chopped parsley"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Lemon Risotto with Margherita\u00ae Prosciutto and Shrimp",
"url": "http://allrecipes.com/recipe/235117/lemon-risotto-with-margherita-pros/"
}
|
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{
"modifier_id": "tconstruct:dyed",
"text": [
{
"text": "改变旅行者套装上皮革部分的颜色。"
},
{
"text": "可以混合多种染料的颜色，并和盔甲上已有的颜色进行混合。", "paragraph": true
}
],
"more_text_space": true,
"effects": [
"多次使用",
"无需槽位"
]
}
|
{"id":"135686236960-34","name":"Kaiserwetter Energy Asset Management","registrationDate":"2020-01-13T17:21:59.643+01:00","category":2,"subCategory":3,"legal":"Gesellschaft mit beschränkter Haftung (GmbH)","web":"https://kaiserwetter.energy//","country":"Germany","headAddress":"Hopfenmarkt 33","headCity":"Hamburg","headPostCode":"20457","headPhone":"(49)4 05 30 56 60","boss":"Hanno Schoklitsch","bossTitle":"Mr","bossPosition":"CEO & Founder","membersCount":20,"membersFTE":"20.0","membership":"BWE Bundesverband Windenergie
\nBVES Bundesverband Energie Speicher
\nWirtschaftsrat
\nDeutsch-Chinesisches Dialogforum
\nUSEA United States Energy Association
\nACORE American Council on Renewable Energy","memberOrga":"","goal":"Kaiserwetter is an IntelliTech company within renewable energy serving mainly investors, financing banks and governments
<br />The company relies on its data intelligence that results from its IoT capabilities to connect machines and to aggregate data for Data Analytics as a Service (DAaaS) with the aim to pave the way investing more heavily into renewable energy to accelerate the emission-free power generation worldwide
<br />Kaiserwetter's digital product suite encompasses the multiple award-winning cloud-based IoT Platform ɅRISTOTELES and ARISTOTELES SKY. ARISTOTELES as its B2B (business2business) offering relies on Smart Data Analytics, Predictive Analytics and Machine Learning to minimize investment risks, maximize returns and create highest transparency standards. ARISTOTELES SKY is Kaiserwetter´s B2G (business2government) product, which uses IoT, Spatial Data and Machine Learning to minimize the energy transition risk and to speed up creating a decentralized green future of energy
<br />Kaiserwetter offers its specialized digital services to all stakeholders worldwide as part of their investment process throughout the entire investment cycle. Kaiserwetter's clients include investment funds, private equity investors, infrastructure funds, banking institutions, insurance companies, supranational organization and also governments as they need to define the regulations for the future of an emission-free power generation 
<br />Established in 2012, the company is headquartered in Hamburg with further offices in Madrid and New York and is currently set to expand into China and India","acronym":"Kaiserwetter","interests":"Banking and financial services, Climate Action, Digital economy and society, Energy, Environment, International co-operation and development, Research and innovation","euInitiatives":"European Green Deal
<br />Digital Europe Programme","lastUp":"2020-01-13T17:22:26.596+01:00","customers":"","costAbsolu":"","costRange":"0-9999","turnoverAbsolu":0,"turnoverRange":""} |
{"id":109065,"date":"2019-10-21 17:32:53","description":null,"for":205,"against":0,"abstention":14,"plenary":4103150,"name":"du jour du mercredi: demande du groupe ID","ref":"Ordre","created_by":null,"updated_by":null} |
{"id":640293,"title":"5 teste medicale pe care trebuie sa le faci in acest an","content":"La fiecare inceput de an, fiecare femeie trebuie sa isi faca un control in ce priveste sanatatea si sunt cateva teste esentiale pe care trebuie sa le bifezi. Testele de rutina sunt cea mai buna metoda de a te proteja de anumite afectuni pentru ca diagnosticarea la timp inseamna de cele mai multe ori o probabilitate de vindecare de 100%.In timpul anului, te lasi dusa de procuparile zilnice si ajungi sa lasi sanatatea pe plan secund. Tocmai de aceea, impune-ti ca acum, la inceput de an, sa faci o vizita medicului. Incepand cu varsta de 21 de ani, o femeie trebuie sa faca acest test in fiecare an. Aceasta evaluare are ca scop depistarea oricarei schimbari anormale la nivel celular si care duce in mod normal la aparitia cancerului de col uterin. Testul presupune prelevarea de celule cervicale, care ulterior sunt examinate microscopic in cautarea de schimbari ce pot produce cancer.Specialistii recomanda ca fiecare femeie sa mearga anual la dermatolog pentru un control de rutina. Melanomul este o foma de cancer cutanat care, desi nu este la fel de frecvent, este cel mai grav. Partea buna este ca odata depistat la timp poate fi tratat. Pe langa controlul medical, sunt recomandate examinarile pe care le poti face acasa, analizand cu atentie daca unele alunite au suferit anumite modificari in ce priveste culoarea sau forma.Cancerul de san poate fi depistat atat prin examinare manuala, in cadrul controlului de rutina sau prin mamografie. Incepand cu varsta de 20 de ani este recomandat ca medicul sa iti examineze sanii, urmand ca dupa 40 de ani sa se faca anual o mamografie. Este recomandat ca testul sa se faca imediat dupa menstruatie, cand sensibilitatea sanilor scade.Afectiunile de inima sunt printre principalele cauze ale decesului la femei si tocmai de aceea este recomandat sa mergi macar o data pe an la medic. Controlul de rutina ar trebui sa inceapa odata cu varsta de 20 de ani, in special daca exista in familia ta un antecedent si au fost inregistrate cazuri de hipertensiune sau afectiuni ale inimii premature. Controlul nu este deloc dureros, presupune ca medicul sa iti verifice tensiunea arteriala si sa iti asculte bataile inimii pentru a depista neregularitati. In cazul in care te-ai confruntat cu dureri in piept, senzatie de oboseala si dificultati la respiratie, doctorul iti va recomanda sa mergi la un cardiolog pentru a face o electrograma.Este recomandat ca o data pe an, pe langa cele doua sedinte de curatare, sa mergi la dentist pentru o examinare parodontala. Scopul testului este de a verifica sanatatea gingiilor. Depistarea la timp a inflamatiei gingiilor nu este esentiala numai pentru sanatatea orala, ci poate sa fie un indiciu pentru diabet sau afectiuni de inima."} |
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{"poster":"Nyvil","date":"2018-09-30T13:45:51.167+0000","title":"duoq gesucht.","subforum":"Clans & Teams","up_votes":1,"down_votes":0,"body":"Add :)\r\n[Silber-gold, ADC / jgl Main]","replies":[]} |
{"pub_date": "2016-01-04T00:00:00Z", "subsection_name": "Politics", "lead_paragraph": "With tens of millions of dollars in contributions to spend, groups are looking to toughen state and local measures in ways that the Republican-led Congress has rejected on the federal level.", "print_page": "1", "document_type": "article", "byline": {"person": [{"rank": 1, "organization": "", "lastname": "LICHTBLAU", "firstname": "Eric", "role": "reported"}], "original": "By ERIC LICHTBLAU"}, "multimedia": [{"width": 190, "height": 126, "url": "images/2015/12/21/us/22guns-web1/22guns-web1-thumbWide.jpg", "subtype": "wide", "legacy": {"wide": "images/2015/12/21/us/22guns-web1/22guns-web1-thumbWide.jpg", "widewidth": "190", "wideheight": "126"}, "type": "image"}, {"width": 600, "height": 423, "url": "images/2015/12/21/us/22guns-web1/22guns-web1-articleLarge.jpg", "subtype": "xlarge", "legacy": {"xlargewidth": "600", "xlargeheight": "423", "xlarge": "images/2015/12/21/us/22guns-web1/22guns-web1-articleLarge.jpg"}, "type": "image"}, {"width": 75, "height": 75, "url": "images/2015/12/21/us/22guns-web1/22guns-web1-thumbStandard.jpg", "subtype": "thumbnail", "legacy": {"thumbnail": "images/2015/12/21/us/22guns-web1/22guns-web1-thumbStandard.jpg", "thumbnailwidth": "75", "thumbnailheight": "75"}, "type": "image"}], "section_name": "U.S.", "headline": {"print_headline": "Battleground Shifts in Debate on Gun Control", "main": "State Focus and Infusion of Funding Buoy Gun Control Advocates"}, "source": "The New York Times", "blog": [], "word_count": "1715", "web_url": "http://www.nytimes.com/2016/01/04/us/politics/state-focus-and-infusion-of-funding-buoy-gun-control-advocates.html", "slideshow_credits": null, "news_desk": "National", "type_of_material": "News", "snippet": "With tens of millions of dollars in contributions to spend, groups are looking to toughen state and local measures in ways that the Republican-led Congress has rejected on the federal level.", "_id": "5689932338f0d845a9e6f1a8", "abstract": "Gun control advocates have won victories in number of states, including Connecticut and Delaware, backed by tens of millions of dollars donated to cause by backers like former New York City Mayor Michael R Bloomberg; combined with Pres Obama's expected use of executive authority to stem gun violence, gun control advocacy has gained new momentum in part due to shift in strategy away from trying to pass measures through Republican-held Congress.", "keywords": [{"rank": "1", "name": "subject", "value": "Gun Control", "is_major": "Y"}, {"rank": "11", "name": "subject", "value": "Law and Legislation", "is_major": "N"}, {"rank": "2", "name": "subject", "value": "States (US)", "is_major": "Y"}, {"rank": "3", "name": "persons", "value": "Obama, Barack", "is_major": "Y"}, {"rank": "4", "name": "persons", "value": "Bloomberg, Michael R", "is_major": "Y"}, {"rank": "5", "name": "subject", "value": "United States Politics and Government", "is_major": "N"}, {"rank": "6", "name": "glocations", "value": "Connecticut", "is_major": "N"}, {"rank": "7", "name": "glocations", "value": "Delaware", "is_major": "N"}, {"rank": "8", "name": "organizations", "value": "National Rifle Assn", "is_major": "N"}, {"rank": "9", "name": "organizations", "value": "Everytown for Gun Safety", "is_major": "N"}, {"rank": "10", "name": "persons", "value": "McPike, Jeremy (1975- )", "is_major": "N"}]} |
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{"poster":"ThomasZwerg","date":"2015-06-09T07:45:46.732+0000","title":"Ekko","subforum":"Champions & Gameplay","up_votes":1,"down_votes":1,"body":"Hallo wie ich weiß bekommt nur Ekko einen Mana nurf\r\n\r\n\r\nStimmt das ?","replies":[{"poster":"Marauth","date":"2015-06-09T08:15:49.562+0000","up_votes":1,"down_votes":1,"body":"hab jetzt mit Ekko keine Erfahrung.\n\nAber {{champion:51}} kriegt nen lustigen Buff: 50% Armor ignor bei der Passive... NETT :D","replies":[{"poster":"OrangeBubble","date":"2015-06-09T11:44:19.411+0000","up_votes":1,"down_votes":0,"body":"\"bei der Passive\",\nwenn die Passive porct oder permanent?","replies":[{"poster":"Veezey","date":"2015-06-09T12:17:40.076+0000","up_votes":1,"down_votes":0,"body":"Nur bei der Passive.","replies":[{"poster":"OrangeBubble","date":"2015-06-09T12:28:22.164+0000","up_votes":1,"down_votes":0,"body":"Klingt tdm nice :3","replies":[]}]}]}]},{"poster":"DuStrischaa","date":"2015-06-09T07:48:30.008+0000","up_votes":1,"down_votes":0,"body":"http://surrenderat21.de/2015/04/vorschau-zu-patch-x-x/\nDa stehn die Patches vom PBE aber Ekko wird halt nicht wirklich generfed.\nWas micht wiederum ankotzt!","replies":[{"poster":"XShâdowFôxnyraX","date":"2015-06-09T08:33:38.899+0000","up_votes":1,"down_votes":1,"body":"du weißt schon das ekko schon generft wurde asl er vom pbe runter kam","replies":[{"poster":"Bergelmir32","date":"2015-06-09T08:42:24.783+0000","up_votes":1,"down_votes":1,"body":"Er wurde auch als er auf dem PBE war nur generft. Und jetzt?","replies":[{"poster":"XShâdowFôxnyraX","date":"2015-06-09T08:52:25.463+0000","up_votes":1,"down_votes":0,"body":"nun kann man einschätzen wieviel dmg er macht und def für ihn bauen was dann auch etwas klappt ist genau das selbe wie bei azir dmg","replies":[]}]}]}]}]} |
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{
"directions": [
"Preheat oven to 350 degrees F (175 degrees C).",
"Put broccoli and cauliflower in separate saucepans and pour enough water into the saucepans to cover the vegetables completely; bring each to a boil and cook until tender, 3 to 4 minutes. Drain each and mix in a 11x7-inch baking dish.",
"Beat eggs in a bowl until creamy. Mix mayonnaise, onion, and 1/2 cup Cheddar cheese into the eggs; pour over the vegetables. Pour melted butter over the broccoli mixture and top with the remaining Cheddar cheese. Sprinkle croutons over the entire dish.",
"Bake in preheated oven until browned and bubbling, about 40 minutes."
],
"ingredients": [
"2 cups broccoli",
"2 cups cauliflower",
"2 eggs",
"1/2 cup mayonnaise",
"1/2 cup chopped onion",
"1 cup shredded Cheddar cheese, divided",
"1/2 cup butter, melted",
"1 (15 ounce) package seasoned croutons, crushed"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Broccoli Cauliflower Casserole",
"url": "http://allrecipes.com/recipe/234281/broccoli-cauliflower-casserole/"
}
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