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Figure REF presents the results for the reconstructed displacement and stress fields for 2 different values of {{formula:541c07dc-d0f8-4a45-b1f1-4c08b224ed0f}} for both the models. We can see that the both the frameworks are able to super-resolve all the deformation fields with great accuracy as the plots show great ... | r | 4a6c407764625b2fccf1aaf3f8b6afc1 |
[label={{formula:204c7235-6c98-41f9-beef-4b5eeeacf101}} ]
Even though the flat limit of the action only requires to consider the corner action {{formula:b3f3d223-8997-4f50-985c-e9af06d71739}} {{formula:0c5fb26e-02ab-451b-b423-22feb0ac80bf}} {{formula:f1287ddc-164a-4412-98e4-55d2cc77b13f}} at {{formula:548bdfc6-e598-... | d | e4a5697d5aa6ab8abf9485092a444a0c |
We have assumed an anchor map {{formula:d64d536a-8ae7-4a35-8e74-dfbbe96b540d}} is injective in this paper. However we should relax this condition. If an anchor map {{formula:86a01bd7-dfc8-4f2e-baa0-f68c38cd54a5}} is not necessarily injective,
we can consider more general algebroid such as a Courant algebroid {{cite:6... | d | 27702cf5be6ddaa665121fd9316b3b08 |
Besides, most existing studies usually rely on a step-by-step beam search to acquire a better solution ({{cite:2c53b90241a71c6aaaa724b5c6efe32e67df6955}}, {{cite:c0658782e502a3f8785513a25baf6d514295da8c}}, {{cite:1974692ba0ce948da6a813f8c597b1e8f4e64cca}}); however, it might not work well on the routing problem with re... | i | fefb99823f1fede38ea3f785ac639320 |
Software: Enzo {{cite:715c8ca1e66fcfd5f06a0ee68ed10178dc3049df}}, HYDRA {{cite:e1316e185316d43ca61f63e76e9e5279e459bfc4}}, {{cite:4f797468a6ba710dd9fe0450405e4122b65e425b}}, {{cite:0071b116fa566b2d43694d55a233ac5769888196}}, {{cite:3fee06d3311b975b3032aeac283a1e8cd8727a56}}, {{cite:41a8c01ef13704c7793d38a42c44932086a96... | d | 495e0b35cb4ab76c43fc46271fcad127 |
Although the approaches mentioned above demonstrate good numerical properties {{cite:4646126efaecee8d1e3b4cb2f962e88487c68860}}, {{cite:179cdc55c9d88f81a60c2a887ad98f9c9cac1b1c}}, {{cite:55c4f310f869fc1ae62c7186de6bed25693f9f02}}, {{cite:df682ea66957024a6f76203ea4946cdf4d20eda6}}, {{cite:3f1ca212a143d1e84bb92445194b1fd... | i | 11430f501865183ca058b1641d65b36c |
The visualizations regarding the trajectory estimates are provided in Fig. REF . It can be seen that our network is able to track the ground truth trajectory significantly better in case of sequence 5. This sequence alongside sequence 7 contain numerous moving objects present in the scene while sequence 5 also exhibits... | r | dc6d4b33700cd5b64144cce05638ce04 |
To demonstrate the efficacy of our models, specifically, the viewpoint-invariant design that helps action models to generalize, we experiment on several major action recognition datasets, including Kinetics-400 {{cite:c780fd94eca5359268eef230c2f6fbf401468343}}, Charades {{cite:58f5f45308cc9ffbfed1ce874074c609e1eb11b3}}... | r | 1c4ada64f96585a71c610c7a386a0b2d |
Underestimation for High KL Divergence
We observe in Fig.REF and Table. REF that, for KL = {{formula:7cf7476e-e685-470e-9710-0827fb753c8f}} , results from both infinite samples and finite samples with complexity control give underestimated KL divergences even though they reduce fluctuation significantly. This is not ... | r | df307384c6f9cfd4a9af54ae33c06a25 |
After the decision trees are trained, we use the package shap to calculate the SHAP values for each feature using the test samples. To compute the SHAP values, shap uses TreeExplainer{{cite:f972c10ba3c0f2ef8fcc7df3f7ad1d3b135f13d7}}, which is a faster algorithm to estimate SHAP values for tree models.
The classificatio... | m | ecc1ffeadd1cbd7df306663edae8819f |
First is the spectral bias. The eigendecomposition of the kernel provides a natural ordering of functions which are easiest to estimate. Decomposing generalization error into modal errors, we found that errors in spectral modes with large eigenvalues decrease more rapidly with increasing sample size than modes with sma... | d | 7c7c10358b9c4a51a544955ce8eddead |
Federated Learning - Drawbacks We will know more about how FL works in the Section . But there are some definite setbacks of FL that require more research, i.e.:
(1) Device drop, (2) Privacy traded off with the utility due to the lack of scalability in the usage of DP. Zhu et al.{{cite:b2041c114e2a08ee72057e63745393edd... | i | 117b2da24f3b0c1833ae65165e1949a4 |
Applications of the proposed approach can be found in various research domains and scientific disciplines, such as agriculture, life sciences, microbiology, earth sciences etc. The approach of generative data for training DL models would be extremely useful for UAV and robotics {{cite:423b387b882908ed658d76ccdf8c16f80a... | d | 67f5d6da94e5971f1b2d0b2a175fa3cc |
In our experiments, we set {{formula:57194384-ee17-4ba8-88bf-a431f66dbe34}} to be a ResNet-18 {{cite:4edd770e539bac7cbd98244c0a8dc42da389e5ad}} up to the global average pooling layer. The architecture of {{formula:4c82dcb5-261a-4ada-9216-0fa8c7762357}} and {{formula:aa35c037-f452-437a-a8bb-646058309b77}} to be a 2-l... | m | 9794078e6f2a957f1207d1d2371ca594 |
For monotone objectives the constants in the two cases are {{formula:734f5ce5-7f41-4357-b5e1-e0345ddbb729}} and {{formula:8a603b3e-3787-4c1c-890b-ce147a789156}} , where {{formula:58399f5d-1c1c-469a-bf59-a66bc1d4fdaf}} is {{formula:7f4512fb-e972-46d9-a904-5eaead12eb44}} , i.e., the best-possible approximation guarante... | r | f12bdab9258c568944cb29039e568264 |
Advances in computational methods since 1972 have given rise to other ways of estimating {{formula:ee4085e7-b2f3-450e-bb72-bb84e88e771f}} in this model.
{{cite:f3b2f225631896edfcaa5064f4460559e05e6340}} describe a Gibbs sampling algorithm for posterior inference.
{{cite:2f84013529b2628d17c0d5bf112fc047f642a263}} descr... | m | 054047654ce591fcd3272ea5dfd7a30f |
On the other hand, one may explain the accelerated expansion through the
paradigm of modified gravity
{{cite:bdfa1c1cc21d6589eb358ab48b739b0383403732}}, {{cite:4fd1a97c498c66105a7cb3e077008eebe1de6ef2}}, {{cite:2867f430d5a552c1e721f1a931cd06d682154e29}}, {{cite:3efe763d7cc23fbeea37bb1f4a88f98996a637ee}}, {{cite:14e6390... | i | f9b46b7f1695734436e82345b07d4a7b |
The results reported here were obtained using vanilla sequential Monte Carlo over the joint space of model structure, parameters, and the latent variables in each observation or experiment. In order for this approach to scale to complex models, hierarchical priors over models, and large datasets, we expect more powerfu... | d | 3a70909dc151d1ea68bebfd6809e5908 |
Here we show how the choice of importance tempering and the position at which it is introduced can impact the geometry of the last layer features and classifiers in the extremely imbalanced setting (i.e., {{formula:36360950-cae0-406d-9eba-e79a4d50c322}} ) considered by {{cite:ee8754e79bd36a8bee5f47f67de8ff227e3efa47}}... | r | 5d432dd2b5e1a3080c27af6358fe7c6d |
We illustrate the overall framework of Multi-Agent Active Neural SLAM (MAANS) in Fig. REF . Each agent first passes its pose sensory signals and RGB image to the neural SLAM module to obtain the agent-centric local map and the pose estimation.
Each local map is normalized by the map refiner and combined with additional... | m | a8d51cd973d74fcccafb0bf5f884188b |
Implementation algorithm for WeightedSHAP Given a finite set {{formula:357284ee-4dee-4e9d-ac0d-88d11d4c1a95}} and an easy-to-compute utility function {{formula:4e78a3e6-b488-44e5-bfb3-6a9ac9f46039}} , the optimal weight {{formula:2ffa4a79-335c-4510-9335-6d9a4298ce2f}} can be achieved by iteratively evaluating the uti... | m | 424c964ac24c36526a2102565f7d7d8a |
{{formula:714704c1-8e6b-4261-b534-1ef3f04ea617}} . By Lemma REF and (), it follows that {{formula:79b8b184-5607-4d92-b097-4dc7c84dea2c}} . If {{formula:16a8537c-be75-431b-a328-76005649e2ba}} , then one finds that {{formula:1e704342-1c29-46cf-b35c-526ffba0dde9}} , so by standard trust-region theory one finds {{formula:... | r | 162e2b68a0867f8fef105835129cf11f |
As opposed to random oversampling or increasing the weight of the minority class, SMOTE was the first method to propose balancing the dataset by adding synthetic minority samples {{cite:7125b982c268c5d2bc834366ff1daad9382360ad}}. In SMOTE, the synthetic minority samples are created by interpolating pairs of the origina... | i | 142369fe09243e513b0c37f02359b381 |
The choice of MLE as an estimator is justified by its large-sample properties. It is well known (see, e.g., {{cite:7d8504459eb5bdcd3f327ce1f47bbd615769d16f}}) that the MLE is consistent (i.e., it converges to the true parameter as the sample size grows) and asymptotically efficient (i.e., its asymptotic variance attain... | i | 7fea38b16a50b4f13d839be42743b6a7 |
In terms of computational cost and ease of implementation,
the gradient descent update has the smallest per-iteration
cost, but it requires running more steps at each grid point,
especially when {{formula:f9c13799-a506-452d-8384-ff4ee833af00}} is large (c.f. Theorem REF ).
By contrast, the Newton method and the ODE so... | d | a5b36d8c566ab2b12cbecb7de455d497 |
FID {{cite:00767af95b694a48915e267b47077bd04155cd5a}} is evaluated by passing an image through the convolutional network Inception-v3 and computing statistics on the average pooled features. Inception-v3 was designed to accept images of size {{formula:916564fc-cb24-4349-9eb1-14420aeb3de8}} , and thus most implementatio... | d | 5dcd5449801f8a1cdcebd2415fc34c8e |
The remaining parameters which are needed to fully define the parameter set are injection and extraction rates, i.e. the rate at which excitons are pushed into the ETC and extracted to the reaction center. The extraction rate can be estimated by considering the time-scales of different transport processes that take pla... | m | c3462fb04debdc841316c90417dfe417 |
This section describes four neural network architectures that we selected from the literature and evaluated on the distortion removal task. The evaluation covers the following models: CRAFx {{cite:740b1d2945c3b0224eb4c0abe31692548c6669c5}}, Wave-U-Net {{cite:50bf084a3688b65f057e9f1a0d102ac35e12101b}}, Open-Unmix {{cite... | m | f3e803d5b6de8b88243b542fa634a3c5 |
Sentence simplification converts complex sentences into simple sentences while keeping the meanings unchanged. We use SARI {{cite:f047b02449a5d422f3e0997ed54aedb61c1a8803}} and FKGL {{cite:4c151486d96b3edbbbec2036488f08dfbdc82f64}} to evaluate the sentence simplification task.
| r | f35642db624f068028b8ecbbd5f18243 |
Our analysis relies on the contraction of hidden representations in total variation stated in Assumption REF . As discussed in Section , the standard Doeblin's condition is sufficient for the contraction {{cite:a00b71ea7e84504d8f5e19432d8b66c790d1eaf3}}. We conjecture that it is possible to prove Doeblin's condition fo... | d | 5bd6603d143eed0c035f43880a83a715 |
Inspired by recent progress in self-supervised learning and semi-supervised learning {{cite:80689d9ee7fceb9f10ea2181a6bba9cb81832c0b}}, we proposed a new self-supervised learning method for our new setting.
| m | 09ec5acaa82b597a89902be87effdbd6 |
Among the galaxies we have considered, Draco and Ursa Minor are affected the most by including pericenter information. These, the densest dSph satellites, have relatively small pericenters ({{formula:a3afe2ba-112c-476e-af97-ffb92bf40680}} kpc) and this pushes their inferred {{formula:c8edf24e-db63-4d9c-b1e6-0cfcece7d1... | d | 0c7b4c78c78f44488fd25f3ff65b9a1e |
Among the exploration principles, randomness is naturally task agnostic, but many sources of randomness need to be designed to decay throughout training to ensure that the source policy converges.
Balanced sampling on the other hand can remain active after convergence, but have downsides as they are usually anchored to... | d | 8e3833fe66dff3e1d029666dff0c5e4d |
defines a gapped momentum state seen in several distinct areas of physics {{cite:215ebbc11a31f5cba0088adf1346be442aaf74d2}}. In liquids and supercritical fluids, {{formula:944ec1cd-84ea-4afc-8350-bd45d96c4687}} is the important parameter governing the existence of solid-like transverse waves {{cite:215ebbc11a31f5cba00... | r | c3b6ef3f99bd12b3d30572cb5945a77f |
First, we analyze how close the pseudo lookahead generated with GPT2 is to the ground-truth lookahead.
For each time step {{formula:58a7b5fa-6535-433f-b86b-479283f80851}} , we calculate the average cosine similarity between the contextual embedding obtained with the pseudo lookahead and that with the ground-truth looka... | d | 8876918ba752057800f3a8266a3b690c |
On the observational side, there has been renewed interest in identifying disk wind tracers and testing the emerging paradigm of disk evolution. See {{cite:4c7afb1c4e51149d2133f60272e632701668f5cf}} for a recent review. Emission from optical forbidden lines has been a long-established tracer of flowing material from yo... | i | f30f07f19491647fad59b2792d85b119 |
An avenue of future research is to combine our approach with dataset aggregation {{cite:f47df1da3548dbeb30548377c0a5a9de29d65dd5}} to deal with the inherent LfD problem of covariate shift between the demonstrator's and the learner's state distribution. Furthermore, it is not always clear what aspects of a demonstration... | d | 2bb03fd777d0f8b8dffb0ca6e2267fc7 |
NLP tasks.: Unified-IO achieves respectable results on three NLP tasks but lags behind state-of-the-models {{cite:93cfec7f81021fd4a3436eeda69a058fa1ae46e9}}, {{cite:ccf89d2437ae92c816db0541313c4b3cd994dd4e}}, {{cite:ca28e7880f248f4af028b361becc43d5c604a148}}. This can at least partly be attributed to scale, modern NLP ... | r | 84302923d740eff8cf65820f1296d93e |
To evaluate exploitability, we made use of the fact that each FP and AFP neural population are made up of agents trained to “exploit” the ones that came before them. Specifically, each agent is trained to approximate a best response to the average policy returned by the algorithm at the previous timestep. So, to estima... | r | a000ecfee071738a6c2a5dfc5a27a958 |
To properly address the overfitting issue in time series forecasting, the difficulty of prediction, i.e., how unpredictable the current label is, should be measured in the training procedure.
To this end, we introduce the target network updated with an exponential moving average of the original network, i.e., source ne... | i | b27227932aadaec589a2256ab86989f6 |
Appendix introduces the BGK (relaxation-type) collisional operator of {{cite:069a65bb76e2de54f8cbfde7bfa245dacb77d147}}, {{cite:4e303b29e52151623b667e434f8e851b6a7ea001}}, which greatly
clarifies the analytic forms of the Braginskii viscosity-tensors and heat fluxes. Viscosities and heat conductivities
of both models ... | i | cc9a0b980d3ae4b317d0768a467de7aa |
We report in Table REF the results for the the three downstream tasks, using 1000 training examples. Those experiments are run using 10 frequency bands, which corresponds to {{formula:290d5ffb-7479-4d0f-b1b7-0ec34ab2d86e}} permutations. In this context, casting permutation inversion as a classification problem is lim... | r | eaef12ee9c18e43bbdaade3c024056ed |
In addition to the methods for generating virtual data and the use of simple machine learning methods such as linear regression, lasso or ridge regression {{cite:9d71b5b7a0b405cdf28d659c79163dda83f33cec}}, other machine learning methods from the literature can also be used in the context of small datasets. For example,... | m | 70ca4c49399619cb072d785e7cdc23a5 |
The training set to determine {{formula:a4b201ad-2daa-4736-8347-7a48ad538fb9}} was then computed by subtracting the gradient of the DFTB electronic energy from our DFT reference property, i.e., {{formula:20a2c1f6-d982-4376-b93c-e3ac5b67e9fd}} . In this work, a spline fit of Ti-Ti dimer repulsive interactions was inclu... | m | 77a8cd4cb4f44629c4293dc22364c8f0 |
Assuming the function {{formula:8d524e36-58c2-4b2c-a01c-5cd411db8977}} to be smooth, we may safely expect the discrete approximation to be close to its continuous counterpart up to an additional error of order {{formula:32cbb7ed-5150-402c-9ed4-ec93857fd441}} , by standard high-frequency discretisation techniques, see... | r | 6a9bbb24b60c8c6ad4f30e67a94ab8a1 |
where {{formula:f8a93110-3031-42c9-aad2-52a904c9e77a}} denotes the {{formula:188679b7-f00e-4a36-842a-2545b1fd3648}} -th row of {{formula:a0c04666-5228-484a-85b3-75ff5fbd8e61}} . The {{formula:ff9ebab0-d802-4476-9ef5-713592a84e1c}} sequence is known as the moving average estimator in the literature of stochastic compo... | r | 49d95dad14867dec60748c7d884bfc2b |
In many networks, the presence of an edge between two nodes strongly correlates with the spatial distance between them; this includes infrastructure networks, transportation networks {{cite:1c3b88c985aa7fcd81d474be7e70ef77858bc3bf}} and connectomes {{cite:3251b5809e877f6213398e2563a7c643a45ed66b}}, {{cite:b3d181ec93461... | i | 3004c956f84de2908ba6a2544507bfc1 |
Since it was first introducted by {{cite:6d4e92ed4ee57d92968649bea21e48396f34a35e}}, sure screening methods based on different model-based or model-free measures have been proposed and shown their merits in variable selection of ultrahigh-dimensional regression and classification problems when coupled with regularizati... | d | fb1440996e9c3d97ba3fba9c94a9ea7d |
SOD aims to highlight the most visually attractive object(s) in a scene, while fixation-based object segmentation aims to segment the gazed objects according to the fixation map, as defined in Sec. .
To illustrate the differences and connections between these two tasks, we conduct experiments on two SOD datasets, i.e. ... | d | 03008403d3030b8ea632607f436e6a24 |
In this study, we propose to stably learn a communication-action policy such that the communication is discrete and sparse according to a limited bandwidth or budget. Specifically, the rate of communication needs to be minimized to essential communication or communication needs to be learned to maximize performance wit... | i | 4bd5ca5716ab1957c6eef881ab69973e |
The values of both {{formula:6aa26e0f-bb93-4c6e-afd6-73e595034934}} and {{formula:3b466bf9-3042-445e-ab6f-bcd8a9c103bb}} obtained in the VDF model at the “matched” {{formula:b56c279f-5a0a-4067-bfd0-764281df2030}} points are plotted in Fig. REF (purple stars), where we also show results corresponding to values of {{... | d | 0280e703f83793dd7cec0973ab1ac002 |
As another example, the classifier was used on stellar spectra to classify them
into 98 different classes as given in the Indo-US Stellar
libraryhttp://www.noao.edu/cflib/ {{cite:d38878dc7a1cf4c7bae70ae37a8e90fbe6b07b88}}. The
input features used were the major absorption lines in the spectra and the
maximum flux value... | r | 7c761bd3c2bc96b109e7064cfd80ecbf |
While in biology various explicit sources of noise exist {{cite:652463df7ef707564d8e839269c0f0b45f899130}}, {{cite:0be6b84ed5513016600d8140f0cb2b97de76aafc}}, {{cite:3c002cc9f9a0ab851519d002c22bb71f8159495c}}, these forms of stochasticity are either too weak (in case of ion channels) or too high-dimensional for efficie... | d | cc509246b4e001fa132f6c13efbdcfee |
Finally, our evidence also supports that tasks can limit a team's collective intelligence {{cite:c2aafc1f8cfc3dbd76b82ef381427315fcf7c816}}. Indirect social learning could underlie parts of team learning wherever knowledge boundaries exist within groups. For example, some teams in studies of collective intelligence div... | d | 7705cdff333bb8e00efd1d36ea36c60f |
In recent years, our theoretical understanding of the statistics of primordial fluctuations has improved significantly. The correlation functions at the end of inflation are now known in analytic form for a wide variety of processes. These advances come from a new perspective toward the investigation of cosmological co... | i | 9239c3b96bcb81f519fa51cc636935fc |
Our results, showing that the best embeddings were obtained from the BEHRT architectures, agree with the huge success the Transformer architecture gained in other studies {{cite:87e950d02ce4cf120dcfba51fdc54d35787fdc32}}, {{cite:5a3bd1b46caaba0a82a65829fce6b3cdef97f4c4}}, {{cite:b77d954921e04411a75557f8c01610b730d578b3... | d | 491e97dd64fc7e264174f866a4ab3a3e |
In the ratings, participants were given various conversations. Each conversation contains three sentences: a speaker’s opening statement, a corresponding response, and a reply based on the previous response. These three sentences can be referred to {{formula:41295fcf-224f-461e-a8e3-eb7dcd6c432f}} , {{formula:4c73f0cc-b... | m | 9516e65ab9aa032cb25ba462b33d1b54 |
Conventional cardiac image registration basically is an iterative-based optimization procedure, which could be quite slow, especially for non-rigid image registration.
DL-based registration procedures can be computationally efficient {{cite:facee99d2a8d3c3c9869eef7ac73efa7af78a84b}}, and have been applied in multi-moda... | d | 2504cfdfc580d34bacd3a21a11a4d1df |
In many applications, modalities may be missing for a subset of the observed samples during training and deployment. Often the description of an object in one modality is easy to obtain, while annotating it with another modality is slow and expensive. Given two modalities, we call samples paired when both modalities ar... | i | 6e836d6fecc8362b04988606e7060a9d |
So far we have introduced the PL-Rank algorithms for estimating the gradient of a PL ranking model w.r.t. a relevance metric.
However, the applicability of these algorithms are much wider than just relevance metrics, in particular, they can be applied to any exposure-based metrics {{cite:2627bd5c3aeef7380af3964235c1d21... | m | 53acb4554e747f5cc8595bd053d612c9 |
To improve the performance of the outcome regression models,
Super Learner {{cite:f9f2ecc489f416b445c4abd508a2139a5dfcacf1}}, {{cite:d89c7fbc1a5a5b43cb80e35c161152f2bc9f9e99}} is often used. Super Learner is an ensemble machine learning method.
We test three different sets of learners for outcome regression models whic... | m | a686a18e571aca87adeb24106638fc3d |
Finite size scaling of {{formula:f4e44701-5909-467c-bcc4-7f6a0fbc79ea}} :–
The quantity {{formula:64c77a1b-1352-47a6-94c2-c5c4c78dbf1c}} , through its dependence on the entanglement spectrum, inherits the information about both short- and long-wavelength properties of the system. As pointed out by Li and Haldane {{cite... | r | 939be5dd4f7bb67644e11b286a822239 |
We conclude that the jets we study here can influence the inner ejecta even if the jets of the first post-explosion jet-launching episode are very weak, like in simulations SN1 and SN2.
The situation is similar to the jets from a NS companion at a close orbit to the collapsing core that {{cite:43f2dcebe2b823baeac43f344... | d | 1c9d2b4cf5ccae39b60a104803324ab0 |
Since the problem we face is similar to the problem of choosing the value of {{formula:2fbfe9e6-2807-49b8-a512-9eaf2b9f3236}} in the k-means clustering, we adopt a widely used solution to the latter, the gap statistic method {{cite:ad0f9705729a4b79fec7270f05bb240cd36111af}}. This method allows us to evaluate if the in... | r | 6b40eb25a1a1b2b4678301d0aae98c42 |
Although the Izsak-Nutov structure is space-optimal,
its {{formula:2d1d1cd7-fd31-4e2d-9eaa-f78cdbdf7716}} query time
and polynomial construction time can be substantially
improved. We design a version of this structure that
allows for {{formula:44683248-3e5a-470c-8c22-1006d7a777fd}} query time independent of {{formul... | r | 756460beb8d7d15cf8429963c85754ab |
Mining strategies are attractive, but inevitably inject some levels of noise in the reference standard {{cite:defd06876c20c6d51d85d307f3c3cb0f83af906d}}, {{cite:54817b3fbd834e1dbd2cc6f12d353bcdbe9db48e}}. For instance, there is no requirement that all the lesions mentioned in the report are explicitly annotated {{cite:... | i | a7a64505de330483fdfb20f53b5745a3 |
Since the discovery of superconductivity in iron arsenide compounds {{cite:7c698bf634a822daadc96880177f89c46ee04963}}, {{cite:e010ad2f346e1f0076799251e4bbd76d97a78fd3}}, {{cite:aed3550104fc8b55e065392558e54cffa71ff2dc}}, neutron scattering experiments have made significant contributions to our understanding of the unde... | i | e6df43dfe306f5be7a7a59a51d2bfcb5 |
Analytical expressions of the nucleon specific energy {{formula:eed6b49b-fab6-49ab-a8e3-fdc5c7127bbd}} , pressure {{formula:eadfac6b-d1c2-498c-ad3e-c48f06c5166d}} , incompressibility coefficient {{formula:8dd2e608-235c-4ed9-8582-c423ee59075f}} and skewness coefficient {{formula:1ee1eae0-ffc7-4a4a-b9ab-33d843b413f1}} ... | d | f1ed65afc179676d95aaf23a98226aa9 |
Limitation. A main limitation of our method is the use of pre-extracted video features, also faced by many previous approaches. Another limitation is the need for many human labeled videos for training and the constraint of a pre-defined vocabulary of actions. Interesting future directions include pre-training for acti... | d | 4a09c326e72dc804a36b5e03ec93ee78 |
The experimental results are shown in Tab. REF . We compare our method with 2-bit baseline TWN {{cite:4ef4761fd626d5c26df9ece68cd1ac9e2f05829d}} on the same framework for the task of image classification on the ImageNet dataset. We also report the classification performance of the 8-bit quantized networks percentile {{... | r | bd57812e5d744b53d4b916d05179a559 |
The direct method means that the dynamics model is learned based on the data collected from the multi-agent environment and the policy is improved based only on the data generated by the learned models. To the best of our knowledge, {{cite:a5f442a1438247cfcf049c27b4dd51266d11295f}} and R-MAX {{cite:a3ab76b59c80f12941c8... | m | df6dfddd425350f482e58e64104a9bf7 |
Deep networks (DN) have become the de facto approach in numerous machine learning problems.
However, by and large, they remain opaque black boxes whose decisions can be challenging to interpret. One example is the colored MNIST dataset {{cite:b18361351d72a7d988dc9b970174fda86e5956c0}}, where typical classifiers align t... | i | 1b1f3fd3dfd868a79404c13fa5decebb |
Most distance-based methods are QbE, for which many representation
schemes and metrics have been proposed {{cite:825b5f3c4724113f859d17cca5e600df1c3339cc}}, but some
recent QbS proposals such as {{cite:71d4184046f43f07ad8af336b42cec436dd0e211}} are also distance-based.
| m | bd6315ce9111b553b800e33a9a183796 |
The overall diagram of the proposed system is shown in Fig.REF . It is mainly comprised of two parts, namely the multiple confidence gates enhancement module (MCG) and ASR. Firstly, We convert the waveform to logarithmic Fbank (log-Fbank) {{formula:ec43f17e-297c-4b3c-a2bb-34d3d89ab599}} as the input to the model by th... | m | cfafedc2590f783fa34cd961d62e040a |
We study the dynamics of flocking by varying the range of the interaction radius, {{formula:88560006-6d5b-4a1c-a85b-7d6a9a7dcc2b}} , in the case of metric and the number of interacting neighbours, {{formula:b1092dcb-be27-47fc-92cd-9684524927f4}} , for the topological interactions.
In our simulations, we consider a grou... | r | 58be88dd4d02cf179513a49d6b8c671d |
Functional neural representations using Multi-Layer Perceptrons (MLPs) have
garnered renewed interest for their conceptual simplicity and ability to
approximate complex signals like images, videos, audio
recordings {{cite:0af50c894e327b825cf2c725a18367796391ecb0}}, light-fields {{cite:0b2ad303ef4e104d3f3af33e39e7c668dc... | i | c23df0f898db1211d2c234f69e23873b |
A limitation of this study is that we only assessed visual perceptibility of adversarial noise under the default setting of the window level and width.
In settings where careful visual inspection of the adversarial example is possible, the noise may be more visible to observers inspecting images under different brightn... | d | f28547ac4d73445318ef84bc7a2c9785 |
Many learning tasks, particularly, but not exclusively, in scientific computing, are naturally formulated as learning operators mapping one infinite-dimensional space to another. Neural operators have recently been proposed as a framework for operator learning. A particular form, the so-called Fourier Neural Operators ... | d | b53d8c12a17e6474befbacf22d612aa0 |
It is reasonable to extend the theoretical approach to
{{formula:e7ec7eaa-a98a-453d-88ca-34dd5b05711d}} and {{formula:a6ae24a7-883d-4e97-aee5-8f8d52ba0e34}} {{cite:12771588040ed1bf734d95f50e96ef1b5a3ec12f}}, {{cite:21acbe135e23ea6a87efce5628168f817cf4e5aa}}, {{cite:775c2429bd216dae66fc55c8df2dbc14e9d4c696}},
where {{... | d | 0d9274cc40e386d520a3f5b276e37017 |
Since the CP symmetry is conserved at the boundary of the fundamental domain, one may expect the size of CP violation to be small
at the nearby fixed point of {{formula:fd670962-4d3d-4600-847e-363fb6d606c7}} .
In order to estimate of the size of CP violation, we can calculate the rephasing invariant CP violating measur... | d | bc5a4df67433b9b42fb368f457793351 |
As proved in {{cite:b4a33f8fdc647e0a1b32ad59112fe8b4b8aad21f}}, problem (REF ) is equivalent to the following energy minimization problem:
{{formula:f691f923-cc0b-4bf8-a291-f05b444f66a6}}
| m | 888a4d7987216c68d912a2a8e503f5cc |
The max-min in () coincides with the min-max for general compact {{formula:0702dac8-a61d-47e5-b8e3-0a86172cd556}} , namely
{{formula:d8faed08-89f8-4592-b74e-9cf0d5e44989}}
This follows from the classical minimax theorem, see the proof of {{cite:5c9b5a8a5051cfbfb61750bd56d27a532b419fca}}.
Let {{formula:caf7c36e-9031-... | i | 663787186ac22bd6a4cdd73836014972 |
Lemma 23 ({{cite:a4b051669a9b13c24c83f5749bcc2568c853a2ba}}, Lemma 4.1)
The number of children of any node of a cover tree is bounded by {{formula:16d122dc-d152-4f10-817b-f9b480b9203b}} .
| r | ceb964aec510b918c0af498a8816d587 |
The authors of {{cite:b272b38f9bab135d50287e678c26b8e6f69fbafa}} observed that agent policies being unable to adapt to each other in competitive environments resulted in oscillations in rewards.
Figure REF indicates that SAM is able to alleviate this problem.
Policies learned by agents using SAM in the physical decept... | r | 9e07583793f730be2d70d272e4cab123 |
In this paper we have derived the discreteness of measured
lengths in strong gravitational fields in a number of BH and
cosmological spacetimes.
In particular, we worked with the Schwarzschild and RN BH spacetimes as well as the FLRW cosmological spacetime.
For the BH spacetime, the strong gravity region is close to th... | d | 81a7c782e3c3a58f44bb8b4f4aa30f58 |
In Figure REF , we show the few-shot classification results of PointCLIP V2 and compare it with PointCLIP and four representative 3D networks: PointNet {{cite:b5f31a4f013e381bec5c520c01436d30d016ee28}}, PointNet++ {{cite:ead6ac9b50cb3d25945d5b6cac07fd78f38c5b65}}, SimpleView {{cite:ba4bd4cb868950cb721dc91909e61e74fcf23... | r | 6ea05b73ffbdac47819910d195231bce |
As far as we know, most existing results focus mainly on the noncritical case {{formula:48e648bb-0ec9-4f76-be29-07a3efd8db4b}} , where {{formula:559af47a-fef6-4543-95c3-81441320df1d}} and the energy functional is coercive. But the existence and non-existence results of minimizers for the critical case {{formula:05b53f... | r | d47fce35700ff730c2cfb7e4efb400f2 |
where {{formula:802d506c-ed93-4eab-8ee8-dd60242ca09f}} , {{formula:81095b60-0dda-47cf-98c5-34370cfb4b50}} , and {{formula:b5975c71-0c28-486d-a374-56c4087b91ad}} are convex functions, and {{formula:0eadc8b5-743f-4ad1-a75a-b115b890c0a0}} is differentiable.
This general problem covers a wide variety of applications in
m... | i | 36178864cfcb6003f1da8c60f2b24b7b |
Thanks to Lemma REF ,
every {{formula:404c6b41-02ed-4be6-a51d-58a40bd680b9}}
with compact support in {{formula:4a63a314-a283-4b59-9741-c3ff18f97e25}} is an
admissible variation.
As a consequence,
the regularity indicated by (REF )
can be obtained by standard arguments.
Therefore, from now on in this proof,
we restric... | r | 4681b0823348ff860518be652381e991 |
As a concrete example, we recall that the agnostic learning framework was originally defined with respect to oblivious adversaries {{cite:4e0888c460825c2ba447ffd52df10ae4014266da}}, {{cite:09eec266c113ab3663ab14deed164b16504a95cd}}. As in the PAC model there a concept class {{formula:e5ad7045-3af9-4826-966d-d9c61e8aecc... | r | 16ca8bf0eddc4cf7e9ac705bfe3127b5 |
To identify the new physics of Dark Matter (DM), the Basic Research Needs for Dark Matter Small Project New Initiatives {{cite:ab58281aa423510274c3814f3c8b3def3446313c}} recommended to ”detect individual galactic dark matter particles below the proton mass through interactions with advanced, ultra-sensitive detector.”... | i | 8e72c87be78c4299d31d789318319d52 |
While our results for the Fe {{formula:af33b0d6-f07a-436e-b478-da2eff458a93}} Wannier occupations and local moments give a robust charge disproportionation in the {{formula:3866634c-43f1-43ac-98c1-a6f7380fdcf3}} insulating phase, a difference of the total charge density {{formula:43b9ef88-f595-4d44-bf47-85624cd99c17}... | r | 5180394db71293bd0fc6f11aaa51e249 |
We note that recently, ideas from geometric functional analysis have also been very successful in producing non-uniform compressed sensing guarantees {{cite:6d9e47d383c5234090de39e31679b00b52475f68}}, {{cite:bfbd2e9120be60463aa862112ae713f28dfe9a22}}, {{cite:f0262b2510f5a70afb12e00be0af2f6a0cb16ac0}}.
In this regime, o... | d | 5237fb1a7563f95b5aff8a48ec8bbc12 |
Word2vec {{cite:5ee3dbde3b700b128eaed8cecd9b4b62eee6a881}} is one famous method of neural words embeddings initially proposed in two variants: (i) a Bag-of-Words model that predicts the current word based on the context words, and (ii) a skip-gram model that predicts surrounding words given the current word.
GloVe is... | m | 2d81ff9c8655604814db45aa8808d73e |
While the PSPI metric does not rely on self-reporting, eliminating one of the aforementioned limitations, FACS coding requires an average training time of three months, with each trained expert taking on average over two hours to code a single minute of video {{cite:4ddf00f2a35b2cfee767694c7ad0d2a1967a9e20}}. In order ... | i | 6f11e0550426426df3791257a6033cf8 |
The control of stochastic environments is a ubiquitous problem across many domains, but remains challenging computationally for the general case.
Stochastic optimal control (SOC) solvers trade off computational complexity, exploitation of domain knowledge, use of simplifying assumptions and/or numerical sensitivity.
In... | i | d93a9d21c1a1e63801024da59a8232f7 |
Fig. REF shows the NMSE versus SNR when {{formula:00e3ac66-c291-43dc-b2c4-506beebdd82b}} , {{formula:c2de169c-a5b1-42b6-9221-f34f71c78625}} , and {{formula:fb91fbbb-9092-4db4-aeb4-690197754d81}} .
The NMSE of the proposed algorithm is lower than those of other algorithms at every SNR.
On the other hand, the NMSE of {{... | r | d1aeeb6e3c5dbe9739bd59cb505052c0 |
There is widespread agreement that a very natural equivalence relation for sequential, nondeterministic systems
is bisimulation equivalence {{cite:29570d0478ae792d529737238e40ca0edebf9162}}, {{cite:66e6d8888272323d1b4710797ec593b3f1886602}}, defined over the semantic model of labeled transition systems {{cite:9c5036699... | i | 23b979250716829931b8cd390c286d7b |
The two agent motion models used in the simulations are the collision-free (CF) model{{cite:dde7a1dbad7887620adf5bb319945fcee26552cf}} and the social force (SF) model{{cite:b464983b4d530231d6142d404bfa8ce4be9def67}} (see the Supplementary Materials).
The CF model is a speed-based model of first order while the SF model... | m | 874b2c72f17f32bf765427b7bc865f5a |
The algebraic regularity lemma for graphs strengthens the classical Szemerédi regularity lemma in two ways. Firstly, there is a fixed {{formula:092cb49b-2968-4fde-8fca-8ee8b53fd742}} such that the error bounds on regularity vanish against a fixed partition of the graph into at most {{formula:f36efe35-77b5-4b76-ab98-fd... | i | 5ec2ee6200508dadf8ba0b2bcaba183b |
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