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We now discuss the implication of our theoretical results. As noted
in the introduction, in La{{formula:03a80b63-441e-4747-b46d-9aa9a9d54810}} Nd{{formula:56a7df75-431e-4a57-8066-4a8930e8f1d9}} Sr{{formula:927e2ac5-84f5-474e-a6a3-40b5e2167780}} CuO{{formula:87d80e1f-2c4e-4e0a-8dbb-a241ae02a7f4}}
system, ARPES experime... | d | 477c895582d8f0a893a0783fea038cfe |
In this section, we detail our method, {{formula:18e818ed-27a5-41a6-b650-a53d47e3302a}} , which is summarised in Figure REF . It consists of two primary components: (1) inspired by RCAN {{cite:94992bc3c7a035ad21c467fb136b9e3a64aee1e0}}, we train a Sim2Seg model that translate randomized RGB images from simulation into ... | m | 5dc02040db1c3dfc4a0fb7aed9d7d3ab |
As an additional baseline, we implement a fixed-topology CPPN with two hidden layers and sinusoidal activation functions and optimize its weights. Fixed-topology networks with sinusoidal activations are capable of capturing fine-grained detail over continuous spaces {{cite:de6cc8910e29815dcb17dee703dbe6bb83c8ae7d}}. Ha... | m | 8fb2fb02c4e7b36901c6c243123194b5 |
3D multi-view consistency. Theoretically, our method is not 3D aware. Nonetheless, for the purposes of portrait reenactment this is not essential for achieving consistent results in various head poses. Given that training videos are captured by stationary cameras, they provide access to a single view of the scene. This... | d | b7ef40a401851cb722ac559cd29383e6 |
From the opposite sign in the bracket of Eq. (REF ), it can be seen that these three equations are mutually restrained. We can directly get the adversarial properties:
Training {{formula:63919007-d556-4f5e-a605-23bd05868ae5}} to minimize {{formula:bfe54f9e-4bec-4d85-b632-a532bb77683d}} (the domain loss) means {{form... | m | 28370744dbd5894a7b771dd2b42cf027 |
We now numerically assess the proposed algorithm on two different models, namely (i) a linear Gaussian state-space model (for which the filter and joint-smoothing distribution flows are available in a closed form) and (ii) a stochastic volatility model proposed in {{cite:2db6c73bda314c247ae670941f22b5a11cdc1d86}}.
| r | 0e5a3e8fa64939e28443f6ff39806e73 |
For the cosmological analysis we use the CMB temperature (TT), polarization (EE,TE) and lensing angular power spectra from Planck 2018 release {{cite:42ef1a2679bd4096b700689457394354434bf6ba}} and the likelihood codes corresponding to different multipole ranges {{cite:958a148ab76517712fe83693658a3c3f154553f3}}http://pl... | m | 66c5b47c1ffbdfbc70086a7e940a9d2c |
Traditional conic optimization methods detect infeasibility by computing matrix inverse (or equivalently, solving linear equation systems), usually as a subroutine of the interior-point method {{cite:dc4f61609815922052af93c581ec7db4a560ebd5}} or the Douglas-Rachford-splitting method {{cite:e4c983196059fcf0910097e028634... | i | c645efacee20d24e751894952bafcea6 |
Without physical randomization, we believe it is best to refer to the
same test as a quasi-randomization test, as the statistical inference
will be inevitably based on some unverifiable modeling
assumptions.Philosophically, it may be argued that true
physical (“ontological”) randomization does not exist; perhaps
which ... | d | 41bdb9b4943b1291c1883ab4da47c987 |
respectively, see {{cite:3e980b170bbecfd84ac1d78aaa4d416427fdeb89}}. Denote by {{formula:2008e9f1-344b-455f-a074-fa62b59ef201}} ({{formula:56e81e30-9186-468d-b229-a6c61e2845e6}} ) in case {{formula:2d41ea8c-19a2-4839-aec7-3ab6e72d4eac}} ({{formula:88fa7e63-d36b-423a-8cc3-22576e46c42e}} ). A measure-dimension mapping ... | r | 29789f0371b4d23c72a6b3cc65f468d4 |
Finally let us mention the connection with another common approach to differential forms on quantum spaces, due to Woronowicz {{cite:53aeb7d08a8351a82a390cd28451e581926fcec8}}.
In this approach, given an algebra with an action of a compact quantum group, we introduce the structure of a differential calculus on the give... | i | bb6806b99d3eefa62d755a82e5ca49a2 |
In this section, we describe the architectures we adopt for calorie estimation as well as our enhancement of these models with the multi-task paradigm.
We use end-to-end algorithms,
meaning:NTF . i.e catcode:NTF a i.e. i.e. the networks operate on the raw food image without intermediate processing steps.
Similar to ot... | m | 4cdc0cb1463caca0a9efb85592d68e17 |
Figure 2a summarizes model results over a range of semimajor axes, and shows that the effect of GEC heating on planetary radius becomes important for {{formula:ac3315d9-d34b-43fd-a91b-304aaea633f9}} , and is capable of inflating planets to radii consistent with those observed. Note that variations in (a) stellar magnet... | d | 7b597571f096f5fe775441e480376687 |
Using (REF ) and (REF ), one has, for {{formula:aa9424a8-e074-4db8-a456-22b70858b671}} ,
{{formula:aa3d91bf-d6c8-492d-a055-722af121a5ce}}
here {{formula:27311bbe-8af0-4249-a5de-e9de6be7136b}} is used to denote a generic positive constant throughout this proof. Define a functional {{formula:93cf72a9-4a61-4f23-943f-5a9... | r | 081a5e45e60f9444cf9a6a2139c55c52 |
The Hausdorff distance is a distance metric for mathematical sets proposed by Felix Hausdorff in 1914 {{cite:0685e2a6c143e2339810c2928580a58d680c31e5}}. It can be used to express the distance between two non-empty compact sets. Many explanations of the Hausdorff distance and how it can be calculated can be found, both ... | m | a7886288fe40979e23041ab9f1509cf5 |
The Riemannian metric formulation for null surfaces fail as they degenerate and one has to resort to Carrollian structures that arise on such surfaces. Carroll group is obtained by a contraction of Poincaré group where the speed of light {{formula:e8c60519-faa5-4d97-bef0-2b62832381c0}} , and the associated kinematical ... | i | dcee6b20cb0db5d936d8a37a2868d47d |
In addition to comparing with the original models of the respective methods, we also compared PSNet with other learning-based sampling methods in literature: SampleNet{{cite:fd3ab7f60ba256f41f94736a1cc396460d4251a5}} and CP-Net{{cite:518f96eb0039126fccc6cb4ff40552a50f9825fb}}. The data structuring part of PointNet++ is... | m | 205e0b4d4301b587a7fc792ad6e3c744 |
Following the common practice {{cite:9e3ce6a56a9a2d914997eefe7c159049170fc71c}}, {{cite:1f0c1d86e4cca650a5917c64ad580d48a18c2042}}, we interpret the MTL task into a multi-objective optimization problem. The optimization objective and its constraints in our method are both based on the mutual information {{formula:1266... | d | b655539d99eac96cd22757455a666d25 |
In conclusion we hope that our theoretical investigation will stimulate
further experimental analysis of triangular, and more generally frustrated
magnetic systems by Raman scattering. Several novel materials with
triangular structure have been investigated thoroughly over the last few
years, among them the cobaltites,... | d | 75fe5710ed51b3ac1863a30931329a6c |
LSTM {{cite:3d13f12c8400fbea2f823e40acd09e8a88242e6e}}: It is a variant of RNN whose name is Long Short-Term Memory (LSTM). LSTM updates user (session) embedding by inputting a sequence of historical interacted items of the user into the LSTM cell, which could capture the long-term dependence of the item sequence.
Ti... | m | 48a308e4495d7b6b91c3b7539a8f37d9 |
COMPAS Dataset. In COMPAS dataset {{cite:229bcac38fea4816dd65bedb4917236446ad216b}}, we consider the same type of fairness criteria, which is Equalized TPR. In this dataset, we consider that the equity is desired among races, which are “Caucasian {{formula:90b091b4-415c-498a-b6c4-6e18d7dc1a39}} , African-American {{for... | r | 53b0607df5d5b93b614aff660d33d754 |
As an application, we establish the local invariant theorem, which is a piece in the Clemens-Schmid sequence {{cite:3c57f322970406c4b6d8890a06b537a12b08eb24}}, when {{formula:31699003-b0b5-4678-9ef9-4427872c02a5}} is non-reduced. The local invariant cycle theorem first was proved by Deligne in an algebraic setting whe... | r | 516bf75ff1fb01487e0e70c903dcb059 |
Light nuclei production in high energy heavy-ion collisions have been extensively studied both experimentally and theoretically {{cite:eba254a1a0cdc6b80cabde7383dbf74f7a379bc0}}, {{cite:31a9b369afbf35bcb50652e928f0aa7e17da8e4b}}, {{cite:1e82e49f74b5d45388beac4fd135e2dff913a83b}}, {{cite:7195223c031506aaae9aa1f1310d7e77... | i | 0bea26efd0505fd8addd2f11b9138d29 |
The conductivity of graphene was computed within the local random phase approximation, which is a function of the frequency of incident light {{cite:b2a4fdd3031b3a199c31df969c4684d7f73f5355}}, {{cite:6efd39f36117fc03f69fafeb50c896053812b25f}}
{{formula:686a67dc-f1b5-473b-badf-4f0fae7d3e1c}}
| m | 0f1467820b772d772af96380638854f0 |
In the OpenAI Gym environment, experiments on 12 Atari games in total were performed with both Pixel Novelty and the fitness-based approach. The specific games to be included in the experiments were selected to represent equal subsets of games, half of which contains multiple obvious local minima (e.g. Montezuma's reve... | r | 45d3abed31c925da63679c20f13bedcb |
PIRL is a global, in-model method used in place of DRL {{cite:45e205fd8cda318a951af903624ed52ab9abde57}}. In DRL, neural networks reflect the policies and are difficult to comprehend. On the other hand, PIRL policies are expressed using a high-level, human-readable programming language. However, unlike standard RL, th... | m | 9022785ce930e5ba08d19629f3ed9aab |
CommNet (Communication Neural Net) {{cite:76869c6ae666fac01e31cc51f36251a18a36510e}} uses continuous communication to coordinate multi-agent system. CommNet is the typical work to replace manually specified communication protocol with a deep feed-forward network.
| m | 073d472994baf3135658501485b60e77 |
Quantitative Results under In-Domain Testing.
We exhibit more results with two settings that under In-Domain Testing, as shown in Tab REF . Specifically, the first setting (denoted as {{formula:b502e527-c077-47bf-bfb4-097023c61d1e}} in Table REF ) is case-specific training but testing on unseen poses, where generaliza... | r | 01cf17ad02414aa56a1aaaefda64902d |
Datasets In a centralized paradigm for visual recognition tasks, there are mainly two types of dataset benchmarking for long-tailed study. The first type is the long-tailed version of image datasets modified with synthetic operation, such as exponential sampling (CIFAR10/100-LT {{cite:629edc0f452f2eedbc732bcd8376ffcfa2... | m | 1a8d4f1fffe01e22f744320d11972d4a |
Lemma 1 {{cite:5e70f139ed929708d861af9b7a71051eb4359773}} Given {{formula:13c2036e-c60c-4d75-b542-b1ca4b727142}} , with {{formula:13d1e66d-2d26-4fe8-910e-b8ba15b4d9dc}} , {{formula:845120af-1179-4ba2-bf5a-8379caa16a8d}} , and {{formula:264f3efa-f563-4adf-947a-ad400b015a42}} .
Assume that the data generating system is c... | r | df4f9dd3f4e0a8bb517f973eff657b9e |
The simplest way to think about discrete dynamics on a network is in synchrony, where all nodes update their states at the same time. Crucial insight can be gleaned by modeling dynamics in this way, for example in Boolean networks {{cite:cb2f9a7cbeb7c07f02cefd07bf1680d0a902d4ed}}. On the other hand, such models can ove... | i | 115b14a37fde5c1641aa5723ed6be190 |
Let us mention that assuming metric regularity vs. strong metric subregularity of the mapping {{formula:ad70812b-1591-466e-b295-517013483981}} from (REF ) ensures the solvability of subproblems in the basic SQP method; cf. {{cite:a2e581a0ba2f1f9ba5e5a2dfb2a7cbd2dcc5080b}}. However, the next theorem shows that in our f... | m | 2b914c69ad435bdb1ce3b8f6e4617006 |
We have shown that in the MNIST dataset a correlation exists between the self-influence score (measured using TracIn) and the memorisation score. Contrary to our expectations, we did not find a significant correlation in our experiments for Fashion-MNIST and CIFAR-10. We suspect that one reason is the influence of shor... | d | 24be99361f122582b7eccb88478c3a62 |
By Exercise 2.12 b) of {{cite:c6bf4948f6d3f52680b23bd905cc1012f1e61637}}, we also have for {{formula:63a24aa0-49f9-4985-94d5-aa1a27dcc0db}} :
{{formula:0b062c14-28ea-425c-8b5b-dcac560ed4ba}}
| r | b11990c569859c7f6750bfb87cddbe35 |
In passing, we note that we do not detect the radio halo of A2065 in our current {{formula:676abb18-0c28-452a-b8bd-1764a2f66f25}} resolution 250–500 MHz band image. This is likely to be due to the fairly short duration of our observing run (just {{formula:8e55f15c-53dc-4c06-beda-3dd334430a79}} hr), which results in p... | d | d5baa85e75f80521df41bea99b409f51 |
The existence of the QCD axion is well motivated by the strong CP problem {{cite:a78b6e68d591a82fc29fd6927bed3f6034bcec25}}, {{cite:ae6c29f47fb870cb3bf6e8f81faa182c964e3572}}. The QCD axion also arises in string theory models, along with a potentially large number of axion-like particles (ALPs) that do not couple direc... | i | 161596f968b7e7c6b8c695285acf154b |
Communities can also be identified by running dynamical processes on the network, like diffusion {{cite:496248424da63cc51e3b70e83b9231482cb0ef89}}, {{cite:9e8bf6f5888bca0c6be1a590b07659a724c7a3e1}}, {{cite:bfa265020745ff2b24f8994ddd74c05434d507dd}}, {{cite:7bb8e19b85336eca3f1a262abc83b6c4168fe1ba}}, {{cite:e3edeff4a4eb... | m | adfb9ac35dc6c686f1782f4c011fd7db |
In many applications, {{formula:5d45e566-e534-4f26-9055-8a135269bc74}} is a multivariate normal
distribution with mean {{formula:00def6eb-d2cb-496e-a318-4edc97e813cb}} and covariance matrix {{formula:9ad53c6c-f2f8-43bd-b32b-fe797d52645e}} ,
where {{formula:ab68196a-2298-4473-942e-a361dbb5af41}} is the identity matri... | r | ac65a3b627d91d6e263c4d74792dac71 |
Bayesian spatio-temporal modeling has been used previously to determine change points. {{cite:53ba17d3f5b55542bbd30049f23569f7fffccd0f}} sought to identify changes in temporal and spatial associations; however, the change points they investigated represented changes in the spatio-temporal dependence processes, not chan... | i | c833710338bef1abbdcaee9b4cee99bd |
One of the simple but novel contributions of the paper is to link the RL policy to firm-specific attributes. To this purpose, the inspiration comes from earlier work on characteristics-based investing.See, e.g., {{cite:5f368699fb0f58becce60849fc41a01f2283f5d8}}, {{cite:1166dac54cd8a3e153c4a3a19169baa7c8abb10e}}, {{cite... | i | 0726be5f048d05fc7d03b8979947060f |
Second, Federated Distillation has advantageous communication properties. As models are aggregated by means of distillation instead of parameter averaging it is no longer necessary to communicate the raw parameters. Instead it is sufficient for the clients to only send their soft-label predictions on the distillation d... | d | 987b1fff2b6a81cebb0010364c8836ce |
As mentioned, in addition to the four unigram dataset, we created complementary n-gram datasets for the two book series and the two task types.
In correspondence with the n-gram detection method used {{cite:d0f1e9afa87b159da9f4921ed794d6f41345ff05}}, in the datasets n-grams are words connected by the underscore symbol.... | r | 5e940e9e441d2a6eb234214cb0e85738 |
as {{formula:31e0e520-db34-4cec-95b8-144526bec8a1}} .
Define {{formula:d39434d7-f2d0-4396-b875-30f4593a5179}} as
{{formula:99706606-bd17-4e96-833e-78d3ac853941}} and {{formula:43fa6814-c158-4b27-a4bf-24bb8bbcefab}} .
Since {{formula:ebbd4f71-065c-4ab7-8bf4-2ce0c7447530}} is a continuous function and for every {{fo... | r | 5621be54a806e1627f46d3459c3d7ec9 |
We also believe that the feature representations can be utilized to recapture the quantum kernel method beyond the tool for solving the scalability issue. For example, as discussed at the end of Section REF , we can relate the data reuploading model with the quantum kernel method by embedding the parameters in DQF and ... | d | 195dd1dcb02eee61eff165b52c39fd90 |
Given into consideration that a small number of simulations tend to dominate
the benchmarking process, the cumulative total for a performance metric over all simulations seem to be too uninformative and misleading.
For this reason, we used Dolan and Moré's {{cite:dd4abd5479a87b6bad9aecae01cc6334bc0c395d}} performance p... | r | da997dff1729bb8b342fce3752f3609f |
Frameworks like Isabelle {{cite:862d829a2ee7cfcde7431eab42b794880e1ba7e8}} and Coq {{cite:90b735ac258f051824c6878537f492b6077824c9}}, incorporate development of formally verified software. There are different solvers and tools developed within these frameworks {{cite:93128166c5f815afb8ecc68dea8c72b391d45313}}, {{cite:e... | i | 8ca2071045d767c857394e9401b7d74b |
Out of our models, ResNet-BB achieved the highest score for the hayride metrics. This suggests the beneficial effect of propagating the image low level features deeper in the network for the task of scanpath prediction. DenseNet-BB is another model which uses skip connections and has achieved the best results for the M... | d | 2e5f2189405266496ad2d652cfa2670c |
Let us suggest a few directions for future work. The current method works marker by marker and is ill equipped to perform model selection. Lasso penalized regression is available to handle model selection for case-control and random sample data {{cite:e3810ee495af16325f539664adb8bb84ea36e6e1}}, {{cite:514b71f19ca9386fa... | d | e4838185b299dddcdeb6bc7f392cea6c |
We next test on the artif and oscigrne nonlinear least-squares problems from the CUTEst collection {{cite:0072a66ee5e59a7c414a60a50645f3ebc8f625ab}} with dimension {{formula:37d852a6-39a4-4293-bf24-dae08987e38e}} and {{formula:f996c15e-1036-4ca9-bf64-f80b9045ef7f}} respectively in both {{formula:bd14b9d5-c6b4-4cab-9c... | r | ca27755244d6ef63ceae74aa2a51b3cb |
Figure REF shows a TSNE-visualization {{cite:8984f62d8ad80cb676103d203f049b183db17a20}} of the embedding features learned from the CNN-model using the Triplet Loss_3 (REF ) variant.
We use the minimum cost multicut approach to cluster CIFAR-10 test dataset.
In the particular experiment example, the total number of clu... | r | 6ff45d3d8fe5a6af7a6ce92bf22c99b9 |
where {{formula:32fe4ab2-eb8c-43b5-924b-71ee1a85a62b}} is the formal (linear or nonlinear) adjoint operator of the generator {{formula:bd36d6b7-cfb1-489f-9512-742f56e03ef4}} of a Markov process on a state space {{formula:d226010e-3042-47d7-9156-fd175f470f05}} and the unknown {{formula:78f00e4f-6fdd-497b-bea0-31f379a... | i | 393a167b92ae943e90e684a370fc62a9 |
As we see in section:discussion, {{formula:6c5f9d19-3209-4331-8a79-36110be210a7}} and {{formula:f625e890-f339-41a8-a50e-883c8138e94a}} are the same order in {{formula:c1c103e0-1b4f-4d48-8c5e-7828e06a353c}} under the uniform class prior assumption.
By applying either the high-probability bound {{cite:fa5e7a61f8955bf9... | r | ed38b3be6e76e0bea276e75ba246a95d |
Graph problems have historically been an area of interest because of their various applications, but as the size of these problems becomes very large it becomes essential to design algorithms suitable for models handling such graphs, such as the streaming model. In the streaming model, the input graphs are presented as... | i | ee9d99f4d9966bf4d01bb56db55d5a06 |
In figure REF , we show the spectrum efficiency of our solutions and benchmarks.
The number of IRS elements is set to {{formula:88c06da7-a1ed-4670-ab11-f1b4bd149891}} , the distance {{formula:5112fd82-8f93-46d7-92e8-4ee00ca0e753}} is set to 200 and the transmit power ranges from 10dBm to 30dBm.
We consider the followi... | r | fe6997dabe431843235415281a82df3f |
GCN {{cite:a796c997c68e85974ecae42750a438b2b271d2d3}} is the first order approximation to spectral GNN model.
GraphSAGE {{cite:9dd9f428ee1b094f8f98a32a7029156cb2307244}} is the first type of GNN that introduces sampling technique, enabling a good model generalisation on unseen nodes.
GPS {{cite:ba0c0264f8f5c6422d687... | m | 022d35eb59dbfa41462bff7d86d5fb51 |
We compare with the following baselines. The unsupervised methods include DB-SCAN {{cite:dfaba090531236dfe6edff1f590c2fcc818ae813}}, ARO {{cite:00e4641cb7cb4531cab1af5af5c5b62ebf3d9324}}, HAC {{cite:5eca603150af66dfeea71a90e1ba78d83d630a1a}}, H-DBSCAN {{cite:cd29840402cd5ffa8a9586897bad9af3c7cc20dc}}, Graclus {{cite:ff... | r | e0266bedbc64efd7dbc7901d2e5eb6bb |
In Table REF are summarized the results of the baseline networks, Efficient-CapsNet and some capsule-based methodologies present in literature. As for the MNIST dataset, also for smallNORB is evident the gap between classical CNN and capsule-based networks. Moreover, again our methodology has comparable results with a... | r | 2781eeef6e4d60c617f62a53848a6253 |
Therefore, for a system driven by a stochastic flow map of order {{formula:e4054a94-3e8f-4b67-8ec7-e0962f663aa8}} , the maximum number of basis vectors to use in a simulation with FSC is bounded from above by {{formula:c2fcbaec-3b53-4d68-85da-de2d484a5f1c}} .
Hence, regardless of the dimensionality of the random space,... | m | c397b79e3d525d0286b1c2173bd71c44 |
According to {{cite:f7871732bef1c43565cfb2554cb94a74076fee96}}, any straight line system is Zykov-planar, see also {{cite:cb3d6a198339c9215b4e0b5ed5d91a319a70f023}}. Zykov proposed to represent the lines of a set system by a subset of the faces of a planar map on {{formula:1ad0e212-9a92-439a-a873-31d7439fe91e}} , i.e.,... | r | 08b628a24d95122cb993d6c27b948694 |
Zhu et al. {{cite:f04f59f2a0c2242405ef998a0ff87ba6f1443054}} firstly propose to use deep learning for feature matching and deep reinforcement learning for policy prediction.
The proposed framework allows the agent to better generalize.
And they propose to train navigation model in a simulated environment for the sampli... | m | a8677c93f609a0e67f8b6d602612c40f |
Our work focuses on the representation of single-relation graphs, which is a different research topic with multi-relational graph embeddings or knowledge graph embeddings, so it is hard to find an appropriate experimental setting to compare them. Nevertheless, to address the concerns of comparison with the trainable cu... | m | a94594ed0288004daf44f1eeabf32868 |
In order to define complexity we have used a measure that was developed in particular for Gaussian states and that is related to the {{formula:0ab037ad-e526-4d26-bf98-1a45f2cfcaeb}} symmetry of the associated quantum mechanics {{cite:2172d333097334faff032890a64f2f596d50a865}}, {{cite:179cd624abf5f99de3e07995f3162d3a29... | d | 85658018dc8ccbe5e8ded6c3d1748700 |
Finally, we remark that other activation functions can be handled in a similar manner by analyzing the mass matrix {{formula:dd54c9f5-56da-49ac-9e8a-79ff80aadf54}} . For instance, a sinusoidal activation function results in a singular matrix (since the set {{formula:6e515f8e-cbd8-4d0f-90e2-e08be71db262}} lies in a two... | d | 71fa478af642cb714c11736128d1b267 |
The availability of radial velocities for many Hipparcos stars has allowed the membership of OB associations to be determined in 6-dimensional position and velocity space. This can be achieved using a model for the spatial and kinematic distribution of the group, such as a 6-dimensional Gaussian or a mixture of Gaussia... | m | e21243a4cf881a4bcf706624ecfcdb3e |
Our results provide a nice illustration of the efficiency of the
twistor double copy, but are of interest in their own right. It is
often the case that a single copy of a given gravity solution can be
found, but not easily interpreted. A canonical case of this is the
single copy of the Kerr black hole, first formally i... | d | 832456d9a39dd74adbcb81b00f5a0b29 |
Watermarking has been applied for digital media ownership verification by embedding digital watermarks into the cover media to be protected. The owner is able to prove media ownership by extracting the watermark from it. Inspired by this, some works have been proposed to protect the IPR of DNN models by means of waterm... | i | 8d9c744740f1dc6a33b7e646d4e8febc |
To capture motion information, typically point trajectories are either formed by tracked image features or dense optical flow.
Then trajectories sharing similar motion characteristics are grouped into coherent motion clusters describing the motion of a particular object {{cite:a4bf32785a1c0cdbc36c2fffbac26078e93c6b00}}... | m | e05de440704a57e433a55809d9f98551 |
MOT16/17.
MOT16 and MOT17 {{cite:53b153f0d0a1895398308c48a81e853b4a1096c4}} contain the same 14 videos for pedestrians tracking.
MOT17 has more accurate ground truth annotations compared to MOT16 dataset.
MOT17 also evaluates the effect of object detection quality on trackers, by providing three pretrained object detec... | r | eb1ea626aa69754d981d0d7a042e6ee1 |
Thanks to the recursion shown in lemma:approx descent, we can follow a standard analysis (cf. {{cite:ebd6bd9ffe2f768faef2f45d3ada917ab412951d}}, {{cite:c37eb5b64baf816d569dcfc7828ad2199cbfe208}}) to establish weak convergence of algo:gm-shuff. Our results in Prop:convergence complement and extend the (mostly non-asympt... | r | a7c51029888797c2d6ec61b72312b4d1 |
Case 1: stochastic differential equation (SDE) {{cite:4ee1714a124fd2121a6cf8cd4ae1f921b0e59057}}, {{cite:08202e3ad7a26b807d24b9f36f13afefb67bb822}}, {{cite:7e4f33f3c37b63129ab9a91b8a35301bb8d947b4}};
Case 2: random elliptic equation {{cite:acd1295474e4c902cb3b7c2d3b19f6499b81c2f9}}, {{cite:983e6b23fd7e5d83e324d7f5f82... | i | a6170fd3c04d9c0168cd689dbfb9b35f |
where {{formula:430b1dcf-7552-4e6f-a35e-fd90fe88570d}} 's are independent random variables each of which is following the standard exponential distribution with the mean {{formula:eabbdd2a-5c3c-471e-a1a2-a210d9cdfd72}} ; see for example, Theorem 2.2 in {{cite:87dcd73fe4662fb6c0d672a8b85d8b44bdb5ab4c}}. Hence,
{{formula... | r | b6121511908dbb036d65336c41d021c5 |
We believe this work on multi-agent communication is of importance to our society for two reasons. First, it extends a computational framework under which scientific inquiries concerning language acquisition, language evolution, and social learning can be made. Second, unlike works in which agents can only learn latent... | d | cb5f40a1f74afee96dac5b574ea96999 |
Note that in order to improve the coverage of speech data, SSAST {{cite:e75df926a7d1f11a8077f6afcfb482518d98435b}} and MAE-AST {{cite:8b9725d4e5a0843c91eef92f07a5676ed507a0dc}} further used the Librispeech {{cite:c78cb0e7eee85a9945621f301537c6db5a6b6094}} dataset, which has around 1,000 hours of speech. Despite that we... | r | da036c4a2a3e92eafd43d29a34f8528c |
Previous work shows that metric neural representations of environments form when an RNN is optimised to predict agent position from agent velocity {{cite:b32377a1974abc5bc47ec1f04b8512c55c0e53c7}}, {{cite:085a351caba3f3cda64f4a0612aff2364eaba21c}} and non-metric representations form when an RNN is trained to predict fu... | d | 06fb45331fa31b419900f1286049f64e |
In the precipitation scenario {{cite:bc7aebcf0304214227a1845836dbbccff29ccc0e}} for AGN feeding and feedback, cool clouds condense and can form stars or fuel AGN feedback when the cooling time ({{formula:9bf137dd-b88e-438e-a3ef-eb90a8f6fcee}} ) is significantly shorter than the timescale for the cloud to fall to the ce... | d | b61d2934eb5ef4592985fc6445b74758 |
It is well-known {{cite:57cafd6577aae5a7e0bdaca712e55883b499b97e}}, {{cite:ac3231ea527dafa64f771489d816a3cc6e6b534d}}, {{cite:46bb32b8db402cd6e0fa04e6c5eecef516fffe5f}}, {{cite:d1478e6c7612262a044cd85b86060c5af1a35735}} that for a suitable time evolution of
the AKNS scattering data the potential {{formula:b7108a1a-6104... | i | e4711a5878b999b15f3f622ada0ca6bf |
We utilize the A3C as the fundamental algorithm combing with the multiagent system to develop our learning mechanism. The A3C algorithm, proposed by Google’s DeepMind team{{cite:f91089327cdbe412ce36657913fc2f6e54f9d6e2}}, uses an actor-critic neural network architecture. It is a multi-process method including multiagen... | r | e66070fa3fdea5581091e07d19ec091e |
Connection with integrable systems is understood better by considering a discrete Fourier transform of the instanton partition function at {{formula:eaf7d3ff-880a-451e-96a0-3cfe47db936a}} {{cite:eb28e1122051464a4351788472746fb5f5079a69}} with regard to the filling fraction, which is the Coulomb moduliThe generating fu... | i | d34c68cf7df316277023a8760bda6c21 |
Several definitions of intelligence have emerged in machine learning literature in recent years {{cite:5df0b2d6ceb22bf65156c2119c3b7a52560ba7ee}}, {{cite:aba170a22d97321666c180956dbb6617ccdddfc8}}. Although many of these differ in particularities, one consistent requirement is that an intelligent agent must have the ca... | i | 305c72cfe4c73371962b227d1339f574 |
An interesting question is whether FL can achieve the same or similar prediction results as CL. If yes, what are the conditions (e.g., the the dataset's size)? Otherwise, what are the guidelines on when we can use FL in place of CL? As our study is limited to the Bosch dataset from the manufacturing industry, we have c... | d | d5970efabff9846084168c458bbbd592 |
At step {{formula:eff549b1-01b9-40b7-aa42-506723f1ade6}} , the residual can be upper bounded by a constant times squared norm of the gradient at point {{formula:5f66f4d7-7aa1-4c0f-9e29-69ee53a2b98e}} . When using recursively this upper bound, if {{formula:69cd8382-dfe2-4e0e-a7b3-df4c8a1fe3cc}} , then these terms cance... | r | a29a2e1049fa4b0291233ea63e2347ca |
Later, Gualtieri {{cite:138c0289406363c4a737f24091da20a930b534a0}} gave a natural description of this geometry using the language of Hitchin's generalized complex structures {{cite:9a703f16496d7dc16f8b327a58bf95aad96f72e0}}, in particular in terms of a pair of generalized complex structures {{formula:39f7cf95-72da-4e2... | i | 9d025377ed497af8f8129e332cbc8950 |
Functional RG (renormalization group) equation {{cite:323c56bd63a518dead39c9fbb8d61c65d849307a}}, {{cite:15b8c2ffff237a8a64420bb28f1f0ed8c3f1858d}}, {{cite:ee4142136787ced0347ceabbb707a2c22fd66d0b}}, {{cite:6b36d1374d86a85a4e286610f8ba567c7b904fa7}}, {{cite:a84456a1cc48438c6d3a735db5469580658ef0b4}}, {{cite:3915d18d166... | i | 85f9564fe21575ae6faa230abe01a019 |
These higher derivative theories suffer from
the massive (negative metric) ghost problem in perturbative regime,
although
there have been many proposals for possible
ways out (See e.g.,
Ref.{{cite:e7c51a4fbecf0a30267f26b7a82e8b60a91f3a98}}
for the review).
This ghost problem is, however, out of the scope of this paper... | i | 4f297c6380c2d9fd4dd4c027e66375bd |
The second comment is on the entropy excesses on group scales (the X-ray-emitting gas has higher entropies in groups than in clusters when all entropies are rescaled to the virial one; {{cite:3851691ba9238daa454025afbb21187df6a877c6}}, {{cite:65522b175c5445da7adcebb7b2fe7f54a2283235}}, {{cite:948f5e04ba2f79a59ae6f290cb... | d | b4ac340e673acb6aac8ab182a552e350 |
Most of the researches on analyzing experimental images of natural sciences are based on feature extraction and end-to-end mapping to obtain valuable experimental target parameters {{cite:eef0493e70ad7197c434d2c5990d39d1ef3ff76f}} {{cite:cb8ce18051ce7be60bd5e813c039e20c908c1a43}} {{cite:3d9f91b409760a712a31096a4188571c... | i | 489f2d281956af0bc3e40876e81bf8a0 |
In this paper we described an Abelian gauge theory exhibiting a confining potential at large distance. This unexpected
result, at least in ordinary Maxwell electrodynamics, is achieved by coupling the vector field to a Kalb-Ramond field.
Furthermore, both fields acquire mass via the Higgs mechanism implemented through ... | d | 9253a51db926cc827fe9e7de4d1c4e00 |
Similar results are also on the Total-Text dataset.
When the shorter side is 320 pixels, the inference speed of our method reaches 84.9 FPS, which is at least 6 times faster than previous methods, while the F-measure is still very competitive (80.0%).
The best F-measure of our method is 85.3%, surpassing current state-... | r | 0db9c1a1c8fbbb96bc8518c6e36c9d13 |
Benefits of grid-based methods, such as the level set methods {{cite:57e6cf1b106073c37ff18ed560988fc43a2aa2db}} and fast marching method {{cite:44426ef49054f563522e910ed494e192dd53ccd0}}, are that the global optimality is guaranteed, and a closed-loop control is provided.
In other words, the optimal control is provided... | d | 2f25b77273ebb324af997a118f6beb8f |
Fig.REF (g) is a schematic of our four probe measurement setup: a bias current is driven between the source and drain external contacts, whilst the voltage difference is read between the two inner probes. A back gate voltage is applied through the bottom (Tr-WS{{formula:65a2d394-7811-422e-b2d9-461f92dd53d2}} or WS{{fo... | r | 503b97e9bcd6cb81ea5d7ed588056da8 |
The participant behavior is modeled using Hidden Markov Models (HMM) {{cite:18e68051d37c47c69c0a9dc2e64cddaad0663d50}}, and its parameters are trained using hmmlearn{{cite:b6029919f198cd889c50d603522680ae2e140de6}} on the treatment data separated in behavioral clusters, while simultaneously trying to find the preferred... | i | 943cbd6cfd8f6ab37a7d072ff315a8d7 |
blackKuramoto-type models have been used in the literature to provide intuition on the blackbehaviour of power networks blackat slow blacktimescales, by providing analytical results that hold in general network topologies.
blackSuch models have commonly been used to describe oscillators interconnected via lossless coup... | i | 6db9b4cd696e570e6319498153efd838 |
where {{formula:5667f652-fedf-404a-8875-124b2f80f45a}} is the regularization parameter.
The {{formula:191b9945-e6c5-40d4-ab52-fec574db178e}} -norm regularizer provides sparsity on the rows of {{formula:2ccd6755-1e67-40aa-985a-65c43d5b00de}} , inspired by the group lasso penalty {{cite:bf3f8d68d1ca900e644a26ccaa6e09130... | m | 8092a1bc8d6a2cdd839864593aa95aeb |
Finally, the fit to the {{formula:7ad72584-6cf3-411f-b8f9-c82924488600}} capture cross sections for {{formula:11dcd62f-1be4-42cd-97de-868b375aa1f7}} Be reaction as a function of incident {{formula:02b25026-e360-4e02-9ba0-49e7758baa38}} -energy in the range of E{{formula:3c90136c-b200-4427-bbc1-f19092dcf6d1}} = 9.0 to... | r | ff3b93c97d353fd13956db56b2e25d11 |
The planted clique and related problems have important applications in a variety of areas, including community detection {{cite:1799ef30cb7ae0513dadfdf2532a96c37a689211}}, molecular biology {{cite:4d8889a9d5ece1270bf75de29ae53b76f4eacd80}}, motif discovery in biological networks {{cite:dfa9c33e9f289cad9117fef71b75f6cff... | i | fb240de704299de35c931fd392126cd1 |
Global dynamics allow the Adaptive Restore process to make large moves across the space, a property shared by Standard Restore. This feature is desirable for MCMC samplers (since it results in a Markov chain with smaller autocorrelation) and has motivated the development of algorithms such as Hamiltonian Monte Carlo (H... | d | c5f7a51bfd8d7e4506f3f208334140ce |
First note that we bring all the vectors to isotropic position by rotating so that {{formula:e73671c1-9d89-407a-883c-bbacd16eb3aa}} . Now by definition for any fixed {{formula:61690dbf-c1c3-488f-8ba9-1d9bda704c11}} , each {{formula:4511e7b2-f7dd-4023-9187-46c7e55b077a}} is {{formula:f40deb86-a732-4762-a2e4-20c35c37023... | r | a234e133e6dc19d68d57a5ec90319b59 |
Although the simulation study has focused on estimators for binary endpoints, the approach can be used for all kind of endpoints (e.g., continous, ordinal, time-to-event, ...) and estimands as long as the considered estimators are consistent RAL estimators. In particular, our method can be applied to targeted maximum l... | d | 9b62e6b6bfe757114f0e41b00662f8d8 |
According to Fig. REF , for any isolated system it is, in principle, simple to compute the microcanonical caloric curve just by considering the definition
of {{formula:a14f8e48-3099-4680-8c3e-989df75fbbdb}} , this agrees with the analytical solution of the one-dimensional Ising model in the canonical ensemble {{cite:9... | d | 958b874968b5127418ee3d7b36f7d533 |
Specifying guarantees on privacy protection is of increasing importance for medical research.
National laws and regulations such as the US HIPAA Privacy rulewww.hhs.gov/hipaa/for-professionals/privacy/ (accessed 07/06/2022) require measures to protect the privacy of health information.
On the hospital level, protecting... | i | df51df52bf0e60caedcdc8a02be22e4a |
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