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Discussion.
Our evaluation shows that learning on monomer datasets, especially when the dataset size is small, is much more challenging than larger datasets as used in the related work {{cite:c182e142a1fed55cd36b1ddacd81aa09311229a0}}, {{cite:c503b5768cb6c279abea6ef073feda049f3a75d1}}.
GraphNVP shows poor performance s... | r | 32336f042511a9acd5341ff595290c25 |
Finally, we conducted a user study to evaluate the quality of generated explanations.
We measured user performance on correctly answering questions based on explanations, to test user understanding of agent behavior.
We also collected user subjective ratings on explanation goodness metrics {{cite:e6062f326ebf003cab4fed... | i | 4923f686cd16e8da4b07d45fba2299e2 |
{{cite:3db310bc334b7bb7221d25d2bc90e6190e559a36}} propose to train trading systems and portfolios by optimising objective functions that directly measure trading and investment performance. Rather than basing a trading system on forecasts or training via a supervised learning algorithm using labelled trading data, they... | m | 01e551eac6e0827431a062a6847df8bf |
One direction for future work is to generalize our analysis to universal dynamic regret minimization (i.e. with arbitrary comparator sequence), which would make the online bilevel optimization more widely applicable. Further, there exist some other regularities in the literature defined in terms of the functional varia... | d | 3f605d228e2e4d0b381bec041cd9488e |
In this section, we follow a linear evaluation protocol {{cite:1e9a08e422b764a2b0022e595bd2a468d2f4cf49}}, {{cite:6bb8060ef40b649c363b6449698ca16eabc05ba3}}, {{cite:e1a638642e77164e902f52cffa1863d2dc475ff2}}, meaning that the encoder weights are kept frozen and we only train a linear classifier / regressor on top. As s... | r | e40f9c2e17425109b8067bb2c2d62379 |
From the experiments we observe that noise can have an unexpected effect on the accuracy of the model – as such increasing noise may not always decrease the accuracy of the model. We believe this can exhibit the generalizability {{cite:772345846bdda8a61ea16c1b2de5c8fc588c564e}} potential of HDFS, whereby it is relying ... | d | d92b1c23decf554bd6edfbb919b4bea3 |
A VQ-VAE by itself is not a generative model. However, it's quantized index matrix
({{formula:e168d452-cbbd-4ec8-9c67-8a6af8ca7051}} ) makes it possible to sample new data with the help of a PixelCNN
{{cite:5fba3cae89842dddbfc587a1825afc68dc4ac47c}}. A PixelCNN is a well known autoregressive model, which is mainly
used... | m | 7ab4e9f3e88497e6e28786ec2566ff8d |
The amplitudes-based construction of the radiated field (REF ), provided in this work, has implicitly used the on-shell condition for the outgoing massive particles {{formula:d3c0cfb3-e750-4d6e-9ef9-3d0ae5f8aa26}} , which discards terms linear in the velocities and higher, in the scattering amplitude. However, for boun... | d | 3f5831b4d5feaf91c4b1da6d49b40385 |
see, for example, {{cite:887b40cf9bb318f66ceb2778cdcd5f61ce2b078e}} p.368. Based on this observation and
taking the limit in {{formula:a26c624a-8c24-4654-9acb-79ed0218e876}} , one can cover the case {{formula:474ee5f5-2d88-4349-8604-459ac367bc70}} and show
the global-in-time solvability of (REF ). This provides anothe... | m | ce5b69b76cdfefe75fe7caccd4e0cf37 |
We implement GCN and GAT using the PyG library {{cite:14a139254c731d3d28347dc99f9a720b951e6602}}
and LP based on its description. For other benchmarking methods, we
adopt their released code. All experimental settings are the same as
those specified in their original papers. We run each method on the
five datasets as d... | m | 22ea0d944c7971a1f2d48478f0d498b9 |
Finally, we address the impact of this effect on the Zemach radius extraction by the CREMA Collaboration {{cite:0cda31ddff2c270ba490d675b85de1e4201d0f74}}, {{cite:0c29bb2c75c2811dbd4ac944a77b71b853f2e60c}}, that measured the HFS of the {{formula:50712e41-ae3a-4d6b-b526-a099ea0f3470}} state, obtaining {{formula:a0d8455... | r | 72300d53835dd87de635a87b22d6f107 |
The combination of clustering techniques and CNNs has recently been successful on small data sets in that it can go largely beyond the performance of traditional frameworks, i.e., performs clustering without updating features {{cite:943bc6d28a2a7bd4a9f1213b29b7a2b0036e2db9}}, {{cite:40acd93dac9baa197a63ca56567d8f085f97... | m | 53d7ec4e03ac209e86575cbbb5bd86e8 |
In Fig. REF , we show the effect of the load {{formula:617635a3-43ab-4992-9839-7a0a910de72b}} on the center cell's throughput {{formula:87e090b9-103e-4075-8516-35e05dddaa9b}} .
All the curves increase linearly till a peak, which is the desired region of operation, and then drop quickly to zero as the system becomes in... | r | 79b5dbe3c3e9b2b2518076123d71528f |
Note that the {{formula:5924b51f-3773-4772-840b-4e6df31b8114}} above is the AdS radius constant. The existence of pressure indicates the presence of its conjugate form, thermodynamic volume {{formula:020033da-0ca1-4646-b67b-f22acaaed6d5}} {{cite:78d6feee5645ec3b30ab8ba9d9fdcb1ecbbbc627}}, {{cite:7a56b69ff5b3028d79593... | i | 43cc5388d85a9f04101cdc70437d8a55 |
Targeted maximum likelihood estimation (TMLE) has emerged as a flexible framework for estimating a variety of causal estimands {{cite:c6174dba53a52ed1f9180cfe93c5ae1165051424}}. Specifically, {{cite:36dc7a0a531518f7e3bf462de817b68505cfb7d3}} apply this framework to estimate {{formula:f4b8a7a7-63b2-45ff-bddb-a84160b2a14... | m | 4f3c49ef3b2df6dff92948f2ab57c10e |
The solution to chemical reacting flows may contain shocks. Moreover, numerical schemes may result in non-physical numerical approximations, e.g. the density and pressure are negative, and the mass fractions are out of the interval {{formula:47b76b30-2c98-4681-b8cf-60b9c659c6c3}} . The non-physical numerical approximat... | i | 51207d1f8c42e20eb25c0c9fd2f202c8 |
The strict convexity and differentiability of the regularized optimal transportation problem makes it possible to prove significantly more general results.
A central limit theorem for entropy regularized transportation costs, centered at the expectation of the empirical cost, was first obtained by {{cite:dd30379c6bc999... | i | 82451fba26d5415bd8b52a9e9bf91951 |
We showed that using linear self-attention mechanisms such as Performer and Nyströmformer in place of a vanilla attention mechanism with quadratic complexity in vision transformers can overcome a significant computational bottleneck that limits the application of transformers for long sequences formed by image pixels. ... | d | 06c70064da918389ac6d731bb9656e91 |
Deep learning has shown unprecedented success in numerous domains {{cite:d85a268cf2441903d09dd703c1ac5575951e81ef}}, {{cite:7f49e174f723b11103afb9028f38a519ecbece5e}}, {{cite:f937739c1bf6e5ff1343524f608eeb8e5de5a6a5}}, {{cite:24b11c3d3949c0a1984b842cec21d5761bdaf1e3}}, {{cite:c5ff3519964d89d5138629df399dc73e12a1ad28}},... | i | 79505329d3e8bc8eea0d58670361e670 |
Remark 2
The fact that the acim {{formula:8ea27fbe-201d-4cca-a193-92ab73b001d8}} appearing in Theorem REF is unique is a trivial consequence of the fact that any acim satisfying the hypotheses of Theorem REF has to be unique. Indeed, to see that this is the case, suppose there exist two such measures. Then by part ... | r | 8ba7187e6475bb090e0bcfe6fba2430e |
In order to check our results, we have derived new semi-classical relations analogous to known semi-classical relations in the literature (also sometimes called the consistency relations or soft theorems, etc.). Some well-known examples are the Maldacena consistency relations {{cite:29ddc7ecc33e67b96b7833a481b631dd06db... | d | 62c016a968275bb468f992a9cde37987 |
{{formula:4ce5704b-cf5c-4d3a-b501-e9f595c7228f}}
OPENet-fast achieves comparable performance to the optimization-based methods on the accuracy, while OPENet surpasses them significantly. For areas with poor texture or severe occlusion, our method perform better.
{{formula:9f2dd68d-18cb-493f-afaf-7cf7bbf208c3}}
Compared... | m | 1fefa42a260293ee6a1549ac7b3c1df8 |
As the approximation ratio of {{formula:d7c4296a-08dd-4698-82af-0c22a6237349}} is depending on the values of {{formula:e26ca354-5b2d-4e80-9a70-cf6ebe414d82}} and {{formula:f4c14c58-b4c7-4453-891c-5c470f9f5163}} , we next discuss some practical outer constraints under which {{formula:06494151-16d1-4a09-b59f-89243c20d0... | d | 2a2fd72fb8e470e37118c28562972bf3 |
Consider the “Sudakov" analog of the gaussian-based parameter {{formula:095bdf7e-6895-42e7-aa75-1ab07febf82f}} : recall that by Sudakov's inequality (see, for example, {{cite:3dc4c7931b58c4eeb5b4e9b205ef5e33c2c43859}})
{{formula:e1b8a98b-5359-41d0-af4d-56cb466e8ece}}
| i | c780bf1a23b2fc6425deb7236dca94cf |
At the redshift of interest of this work, the escape fraction of Lyman
continuum photons is found to vary over a range of {{formula:2dfa7eee-b4ba-4242-b2f9-cb47cafd1762}} with an average value of {{formula:68db9513-fc7e-44ac-93a1-214c7778f4ba}} , as
inferred by the Keck Lyman Continuum Spectroscopic Survey of
star-for... | d | 2c59c6287235708cf52dba40f7624e60 |
We select the best results from {{cite:4f3f0c09cf3d49059ffd0162f8286c4a14277099}} for comparison – for each testing subset, we pick the best accuracy over 7 methods and 3 different architectures including 4-layer ConvNet, Wide ResNet, and ResNet-18. As shown in Table REF , our simple baselines clearly outperform the be... | r | 8e4059ef0ab94fadc3d4d961ff5131b1 |
In sum, the CFB-A yields two key implications for the experimental
site. First, as implied by the increase in the cHPR performance metric,
which focuses on purchases within the first 100 products, the CFB-A
recommends preferred products earlier in the ordered set of available
products relative to the other extant metho... | r | 218edb01ad0e9f37aa783d0ad1727926 |
Table REF shows the comparison between our method and the baselines. It also compares with the methods attended to this year's challenge. While our method overpass all the baselines on nDCG, it falls short on mAP. The MI-MM approach projects both modalities onto a shared action space using linear layers via max-margin... | r | 271af3608170fc4c55b4dfba08aa21fb |
We study the butterfly effect for rotating geometries in {{formula:6fc5f4f9-441f-4b31-b08a-cadbc7ceb869}} by computing systematically the rate of disruption of mutual information at very late times due to in-falling rotating shockwaves with angular momenta per unit energy {{formula:73b03916-4889-4ca1-a32b-045d902fcab4... | d | e6ad97a395facf394cd1069393812ab9 |
In this paper, we have considered the classical double copy
(specifically the Weyl double copy of ref. {{cite:e78a197a7ba226ae7738f59980caa67dd3e786ed}}), and
how one may formulate this in twistor space. This was already
considered in refs. {{cite:6c8b5360e7ce201795ddfeca1a5f0606690a3c21}}, {{cite:6fe0b53c0c3314e1e455a... | d | 14ba6f10a54bc69cbbc2f8cc8575511b |
The most common theoretical approach to studying the correlated states is to start with a continuum effective Hamiltonian, often referred to as the Bistritzer-MacDonald (BM) model {{cite:de0c0d3a48cacdbc4921d1790d9e22fd58a157fd}}, which gives isolated narrow bands for a range of near-magic twist angles, and then to pro... | i | b2c0b6064f84081ab2f61fa6328c954e |
In our application, smoothing provided a relatively small loss in stated precision compared to complete pooling and direct estimation, smaller than what could be expected from dividing the data into non-overlapping aggregates, e.g. 5-year age groups. As such, the smooth estimates allowed for a visualisation that reveal... | d | 7f8d277c2011811cd6c41bde2a9b1fde |
Results
are shown in Table REF .
We compare to variants of USL with {{formula:cebbc4b6-8a50-4f1d-b304-3bcca8469784}} views and ablate RoIMap and the distance transform loss, {{formula:222665d6-4451-42cf-ad85-ffacc61778f8}} .
We report a random baseline which predicts each object as a sphere with random depth {{formula... | r | 8964ddcfffe2c55602cfa9865dbf6605 |
Fixed Regions (DAVIS): The literature considers removal of content within a fixed region of video in scenes with dynamic objects. Our formulation (REF ) can, in principle, be applied to this case (Figure REF ). However, for high accuracy, one requires additional occlusion reasoning in optical flow, which will be subjec... | r | cbe37e4cf497c1d06371e026b66e223e |
Quantum teleportation is a fundamental protocol in quantum information science that has no classical analogue {{cite:d29c96d184245d6017a36a263239e6d9a0680f08}} (see also {{cite:19455258d9d8be8e6881647085f5869c4eeddb6b}}).
It consists of transmitting an unknown quantum state from one place to another by using shared ent... | i | 5545de76ee406b57887c1c4401b551e5 |
In this paper, we have investigated the holographic BCFT with CBC.
The CBC is an interesting BC of gravity, which is elliptic and leads
to a well-defined perturbation theory of `quantum' gravity
{{cite:71f6914d1a1214bbd2507ced20c2dec6506cc871}}.
For simplicity, we have focused on the classical gravity.
We derived the m... | d | 313a563f6a71c74f4c1e8815f3bd244f |
The problem of finding adversarial scenarios (a.k.a. falsification) for CPS has attracted much attention in the past two decades.
Many approaches and tools are developed using stochastic search and optimization techniques, e.g., random tree search {{cite:d963490c6cb46447a235875af8298915a72b6202}}, {{cite:86b544aef90f9d... | i | 8cc101be167181f473de4de0b9ebdf2a |
with {{formula:4b3a8a0f-a1dd-477a-9422-99f4f647d4aa}} , {{formula:7d68791d-c339-41de-a026-b596da421d17}} , {{formula:4727b268-0d43-4698-b452-46dcc9d40a04}} , {{formula:9ac0d234-3b18-46de-bae2-d715aa744617}} , {{formula:7b7cfaf7-51a1-45cc-a88d-f24f42788e0a}} .
Solutions for problem (REF ) are identical to the ones for ... | m | 2ae6c654f6544050a60ef93b6f1d208b |
Having the spacetime action of gravHS-SDYM, we also show that its twistor action can also be formulated as a gravitational {{formula:49f9e988-7133-4900-b999-d2123a5fd9bb}} theory on deformed projective twistor space {{formula:7eeb1a23-9a3b-4203-82fc-52d0c70f1ebf}} . Therefore, the gravHS-SDYM is integrable. This stron... | d | bb011eeb28b7074d96c7d51b303fc468 |
For medical image segmentation tasks, data augmentation techniques are also used in UNet and its variants nnUNet {{cite:fddbbd37d501d13406b081fc6edc9cfb16358b66}}, R2U-Net {{cite:24f28f71df3c4b8abc86bbef16f534f22dbd158f}}, etc. However, these methods are simple and hand-made, and the improvement of segmentation accurac... | i | ee2a030f146a89d7ac5205c8ae89f5ed |
However, measurements of entanglement are difficult to compute in CMT, especially in a strongly correlated system. With the increase of the degree of freedom, the dimension of Hilbert space exponentially increases. AdS/CFT provides a novel tool to overcome this problem in strongly correlated systems. According to the A... | i | 8e60b1344ed89ec1c5a3b16d7ea618e1 |
Metrics. We report the metrics that are standard in the field. For depth errors {{cite:1a0e20175982392e71e8c1d0f081726f2d74f967}}: Absolute Relative difference: {{formula:38ae5328-fcff-4d42-b818-a4740793a65a}} , Square Relative difference: {{formula:df5290d0-1e39-4599-a39b-94cf36f2a2b2}} , Root Mean Square Error: {{for... | r | 141441a5b27e0426146c07eb1afa335a |
To seek more week conditions, we turn to the application of Jang equations (a certain PMC equation) in Schoen-Yau's proof of positive mass theorem {{cite:8394d2d51d7bcc0633d46f52b813b58b5b32b0aa}}. They constructed Jang graphs, graphs of a solution to the Jang equation, via a blow-up process so they can reduce the gene... | i | 6027bd5039c45a5e71ea510ab3617cae |
In addition to the previous discussion, there are some future directions that we would pursue.
First, it would be interesting to see whether one can have {{formula:a0664611-9915-452a-9fa0-dce07b2f6a79}} -matrix description of Abelian topologically ordered phases on the book-page lattice. Note that the generalized K-mat... | d | 6619be9c2065c79525de6b17c7f14965 |
The great successes of the convolutional neural networks (CNNs) {{cite:a934a13d4bf20412f94db3daba901b66aeeb07e9}}, {{cite:90c5a6cce8bc45eed2399623037f24384ebc8139}}, {{cite:a885b785be7c756026391ea79d67244b71b8938e}}, {{cite:6b90763b85e44f173c3461fe4895558a51eca5c0}} have liberated researchers from handcrafting visual f... | i | d9d3fe2fa69062cb0d2ca8d69449f9b4 |
Inspired by prior works on gradient resilience to partial updates{{cite:58fd2fc08dc2e4b7cdee514c293cd86cb0ed8e79}}, {{cite:1020bd5abbe245603f8f12fe23ac86a7071b0b5d}}, {{cite:8a9f1cebdeb2d0bc8d2d3d57d0e5dca08024ff9a}},
we apply more aggressive approximation of gradient computations. This
allows us to further reduce the ... | i | 3964791d44d296216b4f29c6e0ca43ab |
To prove (REF ), let us view each pair {{formula:b337586f-ea51-4d82-af95-cdc49b5a2561}} , as a random tuple with distribution {{formula:63797e0d-0fd6-4f57-a583-4b1d333f0c9d}} , with {{formula:700c59c9-49f9-4650-be88-29c46f78b892}} the Dirac-measure at {{formula:e8eba221-95a0-42ce-a1a6-e46dafff7d4d}} and {{formula:e0a... | r | 379f5ba00a917764f21663a93413a139 |
Since it is natural to use deep neuron networks to learn embeddings for its powerful expressive capability, C2AE {{cite:a440dec63de7fb87adf53e5cff1d8190a68f480c}} performs joint feature and label embedding by deriving a deep latent space, followed by the introduction of label-correlation sensitive loss function for rec... | m | cc9220528df4a231be50a3a64a9d9683 |
In this work, we follow the training settings of DARTS {{cite:344b51800f5ca3f935ac076cfb10196d929a7a05}} for image classification tasks to train networks from randomly initialized weights, for fair comparisons between the searched architectures.
A large network of 20 cells (i.e. {{formula:a0ad4a51-7a36-4642-94ce-6a533f... | r | 8102ae2aea0ba94609c2bf02040f5788 |
Neural networks powered by recurrent cells, such as Long Short-Term Memory (LSTM), have been used to construct state-of-the-art document classification models. Their theoretical capability of ingesting variable-length inputs into a machine learning pipeline has made them attractive to the scientific community. Even tho... | i | 9665a6b0adbd081895171cf4c1d123e7 |
For problems on graphs whose degree grows with the number of bits, the previous arguments do not apply. For the Sherrington-Kirkpatrick model, the associated graph is the complete graph.
Therefore, each clause sees all the qubits at {{formula:4ae0b40c-e4eb-455a-906c-3e038ee1e08e}} , and sees all the qubits as well as a... | d | 6f8ce17c0e06f5f887b0647ad96d5253 |
where {{formula:6886f49f-fb34-418c-93f1-056e3b4dba3d}} is the VOF function that distinguishes the liquid and gaseous phases, taking the value of 1 and 0 in the former and latter respectively. For modelling of surface tension effects, {{formula:4e5863aa-295f-4e13-9ed5-e76aa209ae4b}} in Equation () is approximated as t... | m | c124cc2a6513561092941122116f2f1f |
As the name suggests, massive multiple-input multiple-output (MIMO) or M–MIMO architecture relies on a large number of antennas at the base station (BS). This allows for serving a large number of users. M–MIMO has attracted much interest in the past decade because of its significant potential for spectral efficiency ga... | i | 588343925110624b4a88e8c3a6ca211f |
The detection of gravitational waves (GWs) from compact object binaries {{cite:7bbd5941aa79f731256c0d855ff9c57bf9f9d6df}}, {{cite:79278cdb2c7965d4b3a153051a5e327edb9e3ab7}}, {{cite:ca1e8fe2b2e37cbc27881c7757d8b68c18b7c535}}, {{cite:0fbf5777373525a2f21e1d30a7e2daba89af3257}}, {{cite:f2413bce92d2f888ab24cda4220746bfb280b... | i | 587f5c94d56dc2ff11d6bea309707570 |
Impact of the number of symbols per word. Authors in {{cite:5c459768d22ba876fefdf3cfecb350e14a353e85}} consider a fixed number of symbols per word sent through the channel. However, depending on the length of the words (e.g., the number of characters) and/or the conveyed semantic information, different words may not us... | r | c2bc4fc7d0e8ddef5651366860b66cef |
The error bars shown in the table correspond to 1-{{formula:8e0600f1-b0f6-4e29-af41-46cb9cfdf6ca}} confidence intervals, whereas the upper/lower limits denote 2-{{formula:73d2b00e-aa31-4bb6-83ee-9c42fcb95c0b}} confidence limits. The table consists of four sections, corresponding to the three mass bins selected for st... | d | 4ea44ac6453ddf63505c728640b784f8 |
For the penalty parameter {{formula:c3245734-43a8-4f13-8116-d7a88424c9ad}} and denoising parameter {{formula:df085d7e-3f65-4e96-9ccc-c0557f7431f9}} , generally they should be tuned according to the noise level {{formula:da45a245-9825-4273-94c9-7edf2fe15df3}} . According to the Morozov's discrepancy principle {{cite:fd... | r | bdaea2b954a89a2cdcedd886bc1d700d |
Data Preparation: The data used in this work is taken from tp53 {{cite:91812ab83e4213cf562f1cd695cf07e9b535274b}}, which has a repository of 1054 anonymized wsi of breast invasive carcinoma patients with their genomic, pathologic, and de-identified clinical information. Images with highlighters or other artifacts were ... | m | 6ec816ed88482412d95b2ab1b6726067 |
In this paper, we present a set of controlled transfer studies for determining what makes cross-lingual transfer hard. We focus on three factors salient to crosslingual transfer: the embedding layer, the tokenizer, and syntactic shifts. We construct a set of systematically transformed versions of GLUE (t-GLUEs) targeti... | i | 180606897ae245cfffb89c37ad410fdb |
where {{formula:ee0ea277-22ce-45ed-a2b7-d26fa4a39470}} is the set of quantization levels, {{formula:552e2ddb-2e4c-4d0b-9eb0-723355410794}} is the number of parameters (network weights and biases), {{formula:a81e4833-4f78-4357-a623-72037fbd47eb}} is the training loss (e.g. the cross-entropy or square loss), {{formula... | i | c29b4d47b4624c52a17e63958af58915 |
To the best of our knowledge, no monocular methods have reported results on Waymo. In order to provide a baseline, we extend the official implementation of M3D-RPN {{cite:16140966492a67568f3f3b36f0c5018b93fdce02}} to support the Waymo Open Dataset {{cite:219ecd4679ee7b3d05be7d642f386aa51d4865c0}}. Table REF shows the ... | r | 3d248b172d200272d4eccdb97513b478 |
Since Valiant's seminal paper about the complexity of computing the permanent {{cite:8982d8b20451d827393b17885ddcf08948fdd0ab}}, counting complexity has advanced to a well studied subfield of computational complexity theory. By proving that the problem of counting the number of perfect matchings in a bipartite graph is... | i | 2d00bbedc738559697dc16153a127bd3 |
However, bridging the behavior gap between the simulated world and the real world remains an open challenge.
Manually specifying each actor's trajectory is not scalable and results in unrealistic simulations since the actors will not react to the SDV actions.
Heuristic-based models {{cite:ba3768f7a69c2358653aebb0135379... | i | e5e93a0a77d45f2f6c901f8bc2eed562 |
While BART has been designed to leverage the advantages of unidirectionality in its decoder and multidirectionality in its encoder, it displayed the worst performance in contrast to its reported high relative performance in various generation tasks. While the reasons for it require further investigation we note that th... | d | 895574d92c01c48dcace1b2f58f44891 |
The soft graviton theorem {{cite:f2c1dc8c44f4ee3ac8044b6be3e3ac4365180136}}, {{cite:b636e0a9dce6e2ce7dbc99caf450862b0be1a700}} is a universal formula relating scattering amplitudes that differ only by the addition of a graviton whose energy {{formula:20aa04d3-dada-40f3-8985-be8d360b86b3}} is taken to zero
{{formula:ac... | i | 6f4fd1c9ce656cdc74bc2543352449f9 |
Related work
For bounded {{formula:618ce48f-7a33-4f97-83d4-2abef1e0b259}} , both i.i.d. samples {{cite:8ed5392b2b3d7d0d6c00a1a98c7dfb731eff03c5}} and thinned geometrically ergodic Markov chains {{cite:51907fc26ad47441eb42e23a98e7021f7b14e9c5}} deliver {{formula:7322ec9e-f23c-454c-bc96-5c41fa3af51f}} points with {{fo... | i | 59614eb8da77c245f2b61c8423648b45 |
Most calculations of the particle creation rate from black holes assume a stationary geometry. However in an astrophysical context, matter and radiation will be falling into the black hole {{cite:9923a08155d753d993c4ba6faa3b99a04c08ca83}}, {{cite:bde3a31ad5eac72f5f83fa4572cced165e625d5b}}. This has various consequences... | i | b406af150896fcb61809ce26f2e77d36 |
Mini-val Results. Table REF reports the performance of single-scale testing on COCO mini-val set. With HRNet-W32 as backbone, our method achieves 69.8 AP when input resolution is set as 512 pixels and outperforms the previous bottom-up methods {{cite:0afbe0410846b4446c8e94393dd9e5334810c22a}}, {{cite:41bb302f97b595b2b... | m | 83621b88c52dcc5d9806a08e52df6f7d |
A book embedding of a graph is an outerplane drawing (i.e., a cyclic order on the vertices) and an edge-coloring such that edges of each color (called a page of the embedding) induce an outerplane subgraph.
A graph or vertex-order with a 2-page book embedding is called subhamiltonian {{cite:06926842efba92948e0afe80ca1e... | i | bcef3d128bac32ff09891b0f7c11e5a4 |
We also evaluate on the raw deblurring task in Tab. REF . It is obvious that those SOTAs trained on the sRGB color space have a gap over methods designed for raw deblurring. Even DMPHN_raw {{cite:266707cdb6097b512e80a2fe7278f279ed88144c}} has minor superiority over DMPHN_rgb {{cite:266707cdb6097b512e80a2fe7278f279ed881... | r | 54ca4fe850a918d65fa60bb15058c964 |
Temporal co-occurrence is explored between modalities to increase their correlation. {{cite:a8a06a322e62f0ff38e74f9f74a13074d22a1d30}} and {{cite:b4b94c7db84f23d4c5f7e1f1dadcffdea226d4d7}} leveraged positive samples from paired modality data and contrasted them with others. This has proven superior performance when com... | d | 8346b671644cbaf489927202eaa6bd14 |
Caceres et al. {{cite:3768859cab56bd44480056c91b2c08f4e9972258}} obtained an upper bound for the metric dimension of cartesian product of graphs {{formula:1f22f505-4216-4adb-929d-4dced78b6715}} and {{formula:817b8a59-b459-4220-9a5b-2ec16af93ee3}}
in terms of {{formula:e604a03f-b981-4897-8616-bd4d3f94db29}} and {{for... | i | 8bfc2b9a7509c059c70e3ec82e41a91c |
Earlier studies on balanced neural activity considered a priori the limit of infinitely many neurons in sparse networks {{cite:d9268fb175e3461e9d7161c3882f07bdf288d697}}, {{cite:f330a1719c2aefbeadd954fdf759c985977b51f5}}, {{cite:8b16a9fd19693651bf0d00100cfeb59845be2bc2}}, {{cite:5bc7f019a72553cd2696b3aa9b8481f517d0010e... | d | 28ab05a2f8627930890db54b5cbbd91a |
Quantum computers are expected to provide substantial speedups for a number of practical problems of interest, such as factoring, quantum chemistry, and the simulation of physical models that describe nature {{cite:d0824b50a0a1254e67040a01ecbeef730240d8ca}}, {{cite:36b2554b0f5e9a3913203ef8bf3adedfee34594b}}, {{cite:3ce... | i | 4c2f634b90c34c5a57e1552faf7194d0 |
One way to insert sophisticated linguistic information may be through the use of contextualized word embeddings. While other works have explored the use of transformer language models to predict prosodic and stylistic features {{cite:252d07795fac4d673e5d8f1f9ee5aea56f273e73}}, {{cite:8db5a9f2deb493494db8b994d5fe15a678b... | i | 7dcf8c67722f94980f2ef35ac29908aa |
which gives us the quadratic variation of {{formula:ed21f930-e6cf-4c1a-afd1-a2da7726210a}} . The conclusion follows from the martingale representation theorem (see {{cite:4bc2edcb3c8ad9657bf1f90a1ca070e29d69d0ea}}).
| r | 032a3f6af0496c9a31711efbdabbb460 |
where {{formula:fe1c43ca-7820-4361-a0f0-552b8e6296e2}} is the synchrotron spectral index, {{formula:95baf284-a98b-4077-8d9a-65b5addd4eff}} and {{formula:9a244913-255a-4a42-8700-3cc03c658d0b}} are the amplitudes of the
synchrotron and free-free component at 5 GHz, respectively, and the weak frequency
dependence of th... | r | 07d5e34793aa0658f4a01eb4c25dc5c8 |
However, our experiments showed that convolutional architectures
are not limited in this way, and are capable of generalising
to test data that shares no features with the training data.
Moreover, the underlying principles of this approach arose
from models of visual cortex {{cite:0fcd5cdaaa0de26b810430b46d93dbf3e0d860... | d | 39fae4f2af8b78377e40e1bba68f110e |
Definition 2.10 {{cite:5961aed91a7abc81baa51985abc9274a6ad24274}}, {{cite:69724fbd7459e07fe519684f9073c7c3ec56a42a}}
Let {{formula:9ed760f4-4fe8-43d4-a60c-ee1e94643726}} be a Hom-associative algebra and {{formula:fd3281c7-d6ca-4ce1-9b65-91b1c1515a53}} be a Hom-module.
| r | 88f9841c0cc9d98c1a053c64bbe6f96d |
We extend the universal approximation theorem of {{cite:9b4dec58093331e11410f07c454cea484e34af42}} to Theorem REF , where we show that given any measurable operator {{formula:0aa13cbb-e2cb-4850-871b-ec9278a0fa04}} , for {{formula:fdd8e24f-e10f-40c5-b941-23f4f7e91044}} , {{formula:c3e653e1-1142-4a8a-ae98-6003a0e12623}}... | d | 3c660a55bf72426286aee72817fce2ce |
The framework of learning-based volumetric aggregation of intermediate feature maps has been previously introduced by {{cite:265ee0c2f8247cbbcc68bed7e762effe3a814cb5}}, yielding state-of-the-art performance, but it requires a large number of voxels and high computational load since the final output of the network is a ... | m | cf7556893e6c69aa1113fe175749ea5d |
First, the recent astronomical observations {{cite:ce9ca19e6b818c577bc37f0c6611196392d46335}} found that our universe is accelerated expanding. This result can not be obtained directly from Einstein's gravity and his cosmological principle. Since normal matters only provide attractive force. The most widely adopted way... | i | 21194b0d4b5e4c53bdaffc713380fb0f |
From property REF , we know that the continuous Newton flow
(REF ) has the nice global convergence property. However,
when the Jacobian matrix {{formula:3bd09154-470b-4f4e-a94f-ad491a242e77}} is singular or nearly singular, the ODE
(REF ) is the system of differential-algebraic equations
{{cite:0b9aadf0f703b53c7d3e332... | m | 2b9a72fff157160c187ec7dbeff14afa |
The systematic error budget in our lattice calculation is relatively complete.
The remaining systematic effects requiring further investigation are the neglected disconnected diagrams, the quenching of strange quark and the
use of up and down quarks heavier than their physical values in our calculation. The first effec... | d | 17eb104d8fb6c05cc6ce79c9ee5be7fc |
We also evaluated the augmentations for CIFAR-10 and CIFAR-100 datasets, with symmetric noise {{formula:902fffcd-1978-4679-a1c8-fac2ea462df5}} and asymmetric noise of 0.4. For these datasets we included all the 13 basic augmentations and SOTA methods and their combinations. We also evaluated the use of SOTA training s... | r | 143ce1f3faf94f28e09b8b1f4e568c33 |
The transformer encoder {{cite:74252f0df5d6d7443487b03b3d1e8267bf7b2ca1}} alternates multi-head self-attention and MLP (multilayer perceptron) blocks. These blocks are then intertwined with layer normalization and residual connections (see Fig. REF ), as follows:
{{formula:226a0538-7a7a-4e33-b5e5-8efd4ab0df74}}
{{form... | m | 8722780667446c0651932d3eb2be9679 |
where {{formula:e2661ae5-4cf7-4307-8d70-ba148f207910}} is the number of layers, {{formula:7bc230bc-8c2b-47d0-bf6d-8301823bcdf6}} is the filter size of the {{formula:83454651-352e-4faf-90c0-9f0d131b674a}} th layer, and {{formula:3252c984-af59-41d6-87a3-4964aeecf563}} is the stride of the {{formula:2bb79fc2-3c71-47b8-... | i | b4edfac2c605680ae7cbeb9b9f16c3ae |
Despite its achievements, the theory of dynamical systems now requires new ideas to meet the needs of a scientific community that is increasingly dependent on data. In biology and the social sciences, the availability of huge amounts of data is in contrast with missing or poor classical mathematical models. Recently, c... | i | 41b109ea243e2d4219716b737c653ea4 |
Various methods have been proposed to perform cross-lingual text retrieval, which learns cross-lingual word or sentence representations shared across languages. Cross-lingual word representation methods typically train word embeddings on each language separately, and then learn an embedding mapping between the embeddin... | i | d5112f894692a7133e1b7acdc47f5972 |
Other authors have also considered the age distribution of the GCs in M31. For example,
{{cite:dbcc8c1df9ddea95bab5367b7e8f0f1f3600c180}} discovered that M31 contains GCs exhibiting strong Balmer lines and A-type spectra,
from which one infers that these objects must be very young. {{cite:b1b53f1989f279d2907b80cf318b03... | r | 94d3bf920732b6503063284cbde27f03 |
Shallow clustering-based approaches necessitate the hand-crafting of discriminative features and often require the selection of an appropriate kernel. Recently, with the advances in DL, there have been attempts to extend these classical approaches. Most of these methods, such as Deep SVDD {{cite:c12df7ac09d98ba56c62a1f... | m | f2a6d6ce13bb0b5e29151f3504c3b3e2 |
In order to find the optimal central segmentation model, we evaluate several configurations of parameters typical for FL such as the number of local epochs performed by each client during every training round and the fraction of clients selected by the server during each round. The process of training each model consis... | r | 372f9291063c43d3fcdf4170b5e21f35 |
Using the properties of the occupancy measures, the reformulated CMDP problem (REF ) can be rewritten as an LP, where the optimization variables are occupancy measures {{cite:11f621ff50f147ab9c37bd4ac8ba12b3423307c2}}, {{cite:1396e5b05dcd19b6cf47b6ff9b9ee328173b293e}} . More precisely, the CMDP problem (REF ) and its e... | m | 9219e2572ae2b64558d7c91b3f2f4af7 |
In order to evaluate the performance of the proposed framework for event identification, two different datasets are considered in this study.
The first one is obtained from the dynamic simulation of line trip and generation loss events in the Texas 2000-bus synthetic grid {{cite:3e5b7da540d90d04b340f598211305bd7d6fd1ee... | r | 281cd15bc62d0208401abda0fed665cc |
We test our de-biasing technique on five data sets: Adult, Compas, German Credit, Medical Expanse, and Bank data {{cite:8e26640194a51ab6ac106cbe04a1712bec70f916}}. These datasets represent the two general cases where the majority is privileged and the minority is privileged. For the baseline learning algorithms, we mai... | r | 4da70174b4cf8638818079c64649fc8e |
We used 64 parallel environments for the A2C algorithm's sampling. For all the games, we set the roll out number to 5, the frame stack to 4, the learning rate to 7e-4, the learning rate schedule to linear decay, the minimal learning rate to 7e-6, the optimizer to RMSprop, the epsilon to 1e-5, alpha to 0.99, the coeffic... | m | 437d0e6e0df944d5207f7035d375a1f2 |
Extensions to robust PCA. While our work focuses on matrix
completion, a natural extension is to further consider partial observations
with outliers, i.e., robust PCA. As mentioned, Zhang et al. {{cite:b5a4e739beb03ea9cb65991e3a06c2a6e20dcf9e}}
has studied this problem (with full observation) and provides an error
gua... | d | 166d4efc8debf55e9439d374398218c0 |
We have demonstrated that the image representations extracted from pre-trained deep residual networks can be effectively used for benthic marine image classification in general and kelps in particular. These powerful and generic features outperform traditional off-the-shelf CNN features, which have already shown superi... | d | f22805893ba42d2b7f64e62e7deed9f3 |
Differently from disentanglement methods {{cite:0ebbec87d0a4032b8232e8186cedced51fc0c40f}}, {{cite:ec40d22583c12ec2897b8f5d32260042a7cc55fe}}, the proposed CS-CADA does not need to specifically design modules to extract domain-invariant content and domain-specific style representations, respectively. Our CS-CADA captur... | d | 78e287923517942bd97b2f37b9f377b9 |
The primary modeling parameters for each network architecture are defined in Section REF . The majority of these parameters are constant for all datasets that are modeling. During the training of the neural networks and their OctConv variants, a gridsearch of optimal parameters is not conducted. The objective of these ... | m | 89243c2614cfb5e6086cc67d9ff09bf3 |
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