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The first method built and designed for blind zero-shot denoising is S2S {{cite:60200c297dc9d94eaf4bedba6355fd8ed2ce8c72}}. It is a blind-spot network that uses partial convolutions {{cite:efaa332fab265d5c48f2d2971a6a950f16f4d44e}} to mask out pixels, which is computationally expensive and slow.
| m | 058b7d3e97438d8e20978937829b048f |
When the network is restricted to be a branching, that is, adirected tree in which every
vertex has indegree at most one, then an optimal network can be computed in polynomial
time {{cite:2777601e4a47b813e5c5575891762b62df914f75}}, {{cite:507b115fa77431a270434295eacf7c89c22ad17a}}. Note that learning a more restricted ... | r | 9cae64b51f9215c748aeabfe1bf70bea |
The results reveal not only the new degree of freedom in the experiments
with nonlinear dissipative systems in photonics, but also allow encoding
data in the form of multiple stable SMs with different TSs, and SMs with
fixed TS but different colors (central wavelengths). Such multiple states
may be toggled in a control... | d | 589725d9c0db6d3f574568248c869141 |
3. Why we are often unlucky to have {{formula:3bfcbc64-d127-4e48-8acf-c107ce57595d}}
(1) First, the test sets are almost surely outside the convex hull of the training set because “`interpolation almost surely never occurs in high-dimensional ({{formula:a103ec6e-c630-4f24-8f95-cce3b0ed4abe}} ) cases”' {{cite:cb334fbb86... | d | 7c8ed1dd65fa3468097aa671309bc0f2 |
where {{formula:5fd89d34-a858-4225-b3f8-b95f6271e9d9}} is called a moment order. The multifractal analysis consists of determining whether statistical moments of {{formula:0c56f12b-dcd6-493f-964d-2331d04a548a}} -series of {{formula:40a5730a-3761-4af5-8740-afc52f9b635c}} have power-law scaling with {{formula:7f49db4d-... | m | c0359d84bd7db17ff857728b021bdbd2 |
Can SBP work with other efficient training strategies?
We validate if SBP is complementary with other memory saving methods.
As gradient checkpoint {{cite:dc186b64d3c146691290e4f5e74121b9f4f505f5}} is widely used to save memory, we report the memory and speed of SBP when integrated with gradient checkpoint.
As shown in... | r | 0914069a6b381aff1aa78ffdeadba5e7 |
The area-based registration methods, also called intensity-based methods, register images by directly using correlation of pixel values, mutual information, or transform domain of the image pairs. Usually, the global image or a predefined local window is used to search for matching {{cite:23a54a74b7c70396c83c5ff392ebab... | m | e855cd9a88919036a43cc72aeb357558 |
In this paper, we introduce a modular neural network architecture that divides the task into several sub-tasks, each handling a different type of information in a specific manner. Our approach is similar to {{cite:8f1da6c68dcdbd873e52fd89bdd2521ec00d6bf2}}, {{cite:14d1093b89230f3930f01f3cbe9c7286b3a876a6}} and {{cite:6... | i | 7612c2b4d7ef455db699252fa96f18ec |
The first term is the symmetric exchange energy density
{{formula:125a73ee-ff04-4bd1-af80-adc4cb3a12d3}}
with exchange stiffness material parameter {{formula:c35a953f-36db-46aa-97bf-0edc842819bb}} , where {{formula:64c49ab3-fdc6-49e5-a7e1-d07ea536ea73}} , {{formula:a3093f21-c977-40fd-b29b-3cb7bbb61b77}} , and
{{formul... | m | c0d7f15ad40c020881693c9f6cce1daa |
Since Ads/CFT correspondence calls the duality between the type IIB superstring theory
formulated on {{formula:6cc57f9c-8ad8-498a-b935-41033093cf9d}} and {{formula:aa352dc1-76e2-476b-a6a3-64239525ffdf}} SYM in four dimensions ( which realize
a construction that is coupled with the U(1) gauge field {{cite:eab5702ee6b3... | i | c3b1616af7fcf86b062e277fcec9d40e |
If {{formula:3d81fa1e-82e5-4461-af9e-d6f0a5e0c62e}} , then {{formula:ae1d9b6b-8e0c-4ad9-aebc-f5dfd76626ee}} is a CG-group. Next, suppose {{formula:6569bc88-d835-456e-bc11-1c86a73705cc}} . In view of {{cite:94f66902ee22a5216660975a47c79da122143c39}}), the proper centralizers of {{formula:73d73d92-fc93-414d-b52c-ef88630... | r | 383e401b73825b56378a900131b01c97 |
In this work, we demonstrate a striking result: model scale and chain-of-thought (CoT) prompting are alone enough to achieve SOTA accuracy across a variety of arithmetic and commonsense reasoning tasks. Most previous work combines domain-specific architectures, task-specific finetuning, and task-specific verifiers to a... | r | c1cede31430d3cb1f295560df90afcd2 |
The massive scalability of our approach comes at the price of not being able to recover a transport plan or transport maps. This is because averaging maps/plans of high-dimensional measures projected on {{formula:37c7e3d1-cd54-42d5-9ba9-03b77dfa81ca}} is not meaningful, and is a common limitation of sliced OT {{cite:a... | d | 968b65d6457a0c1acb214c39fc8b4761 |
Dataset.
We used samples from the Autism Brain Imaging Data Exchange (ABIDE) Preprocessed dataset {{cite:d3de3f42011ff3d8ae6e30c6443fe868efa07078}} for our experiments. It contains data from 16 imaging sites, preprocessed by five different teams using four pipelines: the Connectome Computation System (CCS), the Configu... | r | d95e81b7cfff7071dcd76b9a98428d51 |
To further valid the performance of our proposed prior, we compare the tilted prior to a variety of recent methods that achieve top performance in OOD detection for VAE's. The methods we compare against are Likelihood Regret (Regret) {{cite:62ebd7d6058a4750fb0772e76df8b6ab254a9bee}}, Likelihood Ratios (Ratio) {{cite:c5... | m | c1fcfc4e4d412ce4f7e7ed4aa5c956b8 |
Recently, some works have considered the sensing model to proposed a mixed approach which considers the hand crafted as well as the data-driven CS reconstruction. In particular, these methods use a deep network or denoiser to replace the hand-crafted prior, then, this non-linear prior is employed in the optimization al... | m | e1ae4b8a948455fd1477fb9ab69245da |
where {{formula:1e56ab4e-695c-4dd3-9553-b061ed88d03f}} refers to the entropy in the supremum norm, see, e.g, Lemma 2.1 of {{cite:a6e58cd1726641a71c4ef5cd14ac0c43b6bba093}}. Now, by the triangle inequality,
{{formula:b5cd65b0-7839-4440-80a8-83cc5d0efe40}}
| r | 34ee0440a08fdb6688307a1e2d1b88f0 |
Arguing optimality of an algorithm is a two step process: {{formula:f5912e3e-2406-48dc-926d-bb37221a16a8}} estimate the performance of the specific algorithm and {{formula:99d38477-6f42-4c74-9378-c2f9be84a470}} derive a matching lower-bound that is valid among all possible estimation procedures. Beginning with the fo... | r | 6cfeb8503fccb7d0c8f011835fe65c40 |
The observability of the truncated problem is the novel ingredient here for which we trigger some microlocal analysis tools such as microlocal defect measures. Indeed, Hörmander {{cite:62d30e2142069d609008c003c860dcfd4b9fc5a7}} and Duistermaat and Hörmander {{cite:0e6583990ee40618d21e26ac981f69bb5deb9c50}} described th... | i | 0ffe0ac289e2f79cbcaad966a7e93ecb |
with {{formula:79dcfa96-e6bc-4f45-bc64-d000fb03284c}} . An algebraic measure tree {{formula:17f6e749-3f42-49b3-a984-ff4a2c82b13f}} consists of a separable algebraic tree {{formula:004e3013-96d0-4fc6-855e-0481265ac5e2}} together with a probability measure {{formula:987f7e90-b66b-4e98-8398-6d513c24d17f}} on the Borel ... | i | 64ef91d6fc7b834d9d1d5b0f0c4fadf0 |
In Refs. {{cite:2eebdc6223d8c30b9ef582199f640eb4ab46591b}}, {{cite:4a7b81e64d9c3e6b7b66ab02eb7908125f72f2a8}}, the authors study the analogous heavy meson systems.
In Ref. {{cite:2eebdc6223d8c30b9ef582199f640eb4ab46591b}}, Liu, Luo and Zhu study the S-wave {{formula:5966f158-caa7-43fb-973e-7c1564fcfec3}} system
throug... | r | 19bd53e2284dedf02b4ae2d3e1690fc7 |
being unnormalised kernels. By convention, {{formula:bdadc592-876b-48de-897c-a4abe96de950}} .
Note that each {{formula:51efc1c5-aeb7-47e2-9063-a0651c83f60f}} is a probability measure, while {{formula:ea84ec76-cee4-4c41-b316-53497a609b2a}} is not normalised.
For every {{formula:1a7fd2fb-b18f-45a7-8835-17b07c126ee9}} ... | i | 2b25b57b163a576a7fc8506fa7ea14e9 |
Generally speaking, the analysis of black hole X-ray observations requires fitting the data with some theoretical model in order to measure the properties of the system. Some of these theoretical models rely on assumptions that may be violated in the presence of new physics. In General Relativity, we have {{cite:ca7442... | i | 9aadc8d0dd368f12459d6ec04aa187b0 |
RSC has two other main advantages in comparison with other classifiers. Firstly, by using prototypical vectors the model is intuitively understandable (see for example REF E). This is a desirable feature to protect against overfitting or flaws in uninterpretable "black box" models like DNNs {{cite:4f42619e55449c96c1df7... | d | ff8d4a18386567b13b651d5e54665da7 |
The precision-recall curves of all methods are reported in
Fig. REF -a. As shown, our method significantly outperforms the
state-of-the-art both on the FBMS dataset {{cite:a5c8db5e2c4752cbfcb4c292835bf0652ecc791d}}, and the DAVIS dataset {{cite:d5203c1e90cbbe45f0fd1266eb5e307a87bef355}}. Our saliency
method achieves th... | r | 6c9a05136776cefcd4378b5cc56d8574 |
Other research has pointed out that neural networks also demonstrate an over-reliance on superficial regularities {{cite:c7380f1af31e529ed53f0f4b9f996a33d26a8b3f}} and textual cues {{cite:188f2c0958521edfa296543488b4da8322184641}}.
We observe that the color-shifting procedure proposed in {{cite:44086298b996dc866b4999cb... | d | d123664a86faed405b0d6ba3fdc01b80 |
The aim of the work presented in this paper is to design sparse, low-complexity neural networks by reducing the number of parameters while keeping performance degradation negligible. Memory and computational requirements in particular complicate the deployment of deep neural networks on low-power embedded platforms as ... | i | 56fef51fc7af0ac4613fde2c7640ebad |
Before concluding, we would like to point out how our model can be significant to quantum many-body systems.
Our intention is to indicate how broadly applicable the concept of quantum dissipative adaptation may become.
Firstly, we notice that the {{formula:a14c9181-8563-4ab3-aa1c-1a8b0d8586f1}} structure of energy lev... | d | c4e446278c3f59fbc732baac3b758cd1 |
The value obtained for the mass-to-light ratio of the lens in
Section of {{formula:b39d7b6f-e093-40a5-814f-6238a1cc1784}} assumes a redshift of
{{formula:5ee7452a-892e-421a-b71c-cf12ac357cba}} based on non-detection of the lens in the {{formula:19823b9a-d579-4ac0-8a9e-e92372b53f65}} -band. As this
redshift is essent... | d | 7b8f8b4febd9ed97c6072b8cfc0a4f77 |
Speech signals are corrupted considering SNRs values ranging from {{formula:9bfca399-6c8c-4aed-a806-3a4fcb995683}} dB up to {{formula:bf169000-79b3-45c3-a8bb-3205f7300268}} dB, where the SNRs are measured between the reverberant speech signal and the background noise.
For each reverberant signal, SNRs are selected in... | d | 072b120472e4b22b3430ebfcf45dc6a2 |
As widely known, due to the non-commutativity of the Hamiltonian with different times, the obtaining of desired evolution in two-level systems has still encountered great difficulties. Fortunately, there was already a few famous cases which has derived the exact solution with different restrictions, which may finding a... | i | 33706da34db3aea4d35ec42bca92268b |
The methods and results of this paper can be extended in different directions. We can apply the abstract framework presented in section to other examples of differential equations, for instance the Navier-Stokes equations of fluid dynamics. Although we showed that the curse of dimensionality is broken by DeepOnets for... | d | 9231b43dca07d2e3f24909a8e3d0db22 |
The application and ubiquity of noble liquid detectors in the fields of high energy physics {{cite:84633d4ba4db830bd3f38f13beff3c18452fa4b9}}, {{cite:ac5fb2689fab0ee2e41d0dda02db3fb8bb17e087}}, {{cite:ec7a7fac39a58407935d9a928d1bccc13ab3fa9b}}, {{cite:3426d07f9994270fdc16c9fa915778fac9224f79}}, {{cite:0d3016e3df0fe3c28... | i | c6831f49fce6695b1495c62556679f40 |
Recently, supervised deep hashing methods {{cite:e1e5b5e28b90ac86f622519f0a06ddd77fb7ce53}}, {{cite:eb2a858bc71ee622e2e4b641081104b29c1a669a}}, {{cite:5d69e4bd351fd94c67ebe7ceca09edf902c94c82}}, {{cite:f9277a66082d795a63e15a02b2d2efe6a082ad5c}}, {{cite:ddd21fd441a964be5f7704deb1624de3af4cbbd1}} show promising results f... | i | 5464aaab344a9db0c74678aca8ae67e9 |
Datasets and Evaluation Metric. MS COCO 2017 {{cite:2237af9992594f5da9e693225e5426b3cd94a602}} is a challenging benchmark in object detection which contains 80 object classes. For experiments on the COCO dataset, we use train and validation set for training and test set for testing. The standard COCO protocols are used... | d | 438b80036a9bf52b70aa0aef8b8dc000 |
Thus the aforementioned two classes of functions exhibit lower/subdifferential regularity, while the latter collection of extended-real-valued functions is much broader; see, e.g., {{cite:2b2c18bf7f06d7bea27446e33c9e5171248dd4cb}}, {{cite:01a2f8a5c2e789277b64d701f30be05929dd4966}}, {{cite:b647e02a3e5f8041d11b00cd668480... | d | dc5da8d30f920bd1ca7017b901433a06 |
Contrastive Learning experiment: We next evaluate our HyperInvariance framework with a real-world contrastive learning experiment, taking SimCLR {{cite:5957acd12f0646ef757c1ea903d085cbb59ceb12}} as a representative state of the art learner to build upon. To define a set of invariances of interest, we borrow from {{cite... | r | 84cc9882c636256900115531933d7209 |
It is relatively straightforward to interpret the scaling trends in terms of
the internal shock model in which the basic units of emission are assumed to
be pulses that are produced via the collision of relativistic shells emitted
by the central engine. In the case of the pulse-fitting method this is
essentially the de... | r | 1888522046623aeebe2fe2450c821daa |
To incorporate the social preferences or personalities information into a multi-agent control framework,
some researchers draw ideas from sociology and psychology, for instance, the concept of Social Value Orientation (SVO) {{cite:05fa559743261d76f9ae2dd005fabe1c901e30c4}}, {{cite:2e68b7a2b5764c58bf0a839adf2d65bd00fb6a... | i | 8813443bfbac16fdf821deca3b6837e4 |
This variance is a measure of the uncertainty. Thus, we want to compute
the partition function. However, the partition function contains an
exponential number of terms and therefore is impossible to calculate
directly. In the next section, we present an algorithm that approximates
the value of this partition function u... | m | a22cf9ea19bda19b7246a83f37862c39 |
Recent results ({{cite:1914bff9798abe992eeedf1795861af6ed90997a}}, {{cite:9689221389074d9b662bf0f7f1ed0e5f7db27af7}}) have shown qualitative differences between the adversarially robust boundaries of MNIST and CIFAR-10, which also impact the experimental findings in this work. In short, a robust decision boundary is in... | r | 97b9024b23b775163568c9a36d4fa7b4 |
EASGD has been proven to be stable {{cite:5ffdfcd861f4866e388d6a128848a2fd689bbf54}} in cases of distributed deep learning. It induces an elastic force that does not allow the local model's weight matrix to deviate too much from the global weight matrix whereas also allowing some independence. The proposed method incor... | m | cb7b4c58674884f734ebb0e8be184807 |
For this reason, we solely focus on the residual error between the solution of Koiter's model and the averaged solution of the original three-dimensional model. We use conforming finite element to discretize the three components of the displacement(cf. , e.g., {{cite:3110509f0970120be852c3d5e3ed4580abebad19}}). Apart f... | r | c2e13838afc55ef958506d3cfca4a552 |
Now we have many different kinds of interpretation methods to choose when we want to analyze a neural model, although they are still in need of further improvement. At the current state of the art, which method we should choose still does not have a definite answer. The choice of the right interpretation method should ... | m | 7ab919c0d453b2e48d9995be47191e24 |
Our study and the previous work described above {{cite:5e4277fada4ceac3740db5f5001dc140cb47bf59}}, {{cite:f1241fb62743cd881bc3cc101ea4f1bbe7e3b530}} incorporates homeostatic synaptic plasticity, but does not account for any other of the wide variety of synaptic plasticity rules observed in neural recordings. Other work... | d | a840ee5abd0a57ffc3ebe56815b41f6f |
FID was adapted to assess fidelity of the generated audio in {{cite:7df7aac0b521e6a734a52f12a28537097bb7c0b5}}. This metric is designed for
very short sounds (<1 second) and, therefore, has limited applicability for long audio as it may miss long-term cues.
Another challenge in the visually guided sound generation is t... | i | d6756e1493eaf2f0918409715938d5a4 |
In summary, we have shown that recently developed methods for
calculating limits on sesquilinear electromagnetic
objectives {{cite:bccb6c3a8c0a767daa6a307efd3d1887a20cbc15}}, {{cite:8c8a71c89e03c70d7513aa489a637e7293b9e329}}, {{cite:e45e3e1bddadb7697c89ed7d435c8ef04b563c60}}, {{cite:95ec1e32f170debd16c5e5159e8c53e8a1c7... | d | cc91f0adebd5450668e78c52e3aca56d |
We extensively studied the vacuum structure of 4D effective
field theories arising from Type IIB flux compactifications
on the mirror of the rigid CY threefold.
Since all the closed string moduli can be stabilized by three-form
fluxes themselves due to the absence of Kähler structure
deformations, such a class of flux ... | d | 39d1f826ac3f5eff80a74b0bf474d53e |
A comparison of the resolved and boosted channels (although corresponding to different phase-spaces) is possible at the parton level in the form of a ratio to the NNLO QCD predictions {{cite:c3d6c5614c9efcbd600942e1318a277d440b01a2}}, {{cite:d1da465b6e267ca064168bf8c1b122412a0941e3}}, {{cite:5ac1b274496feb1270708584cfc... | r | a88cd8925aeade7e5b61523ce2b0791d |
and {{formula:51dae330-b2ef-4b9a-b460-b59651a5bfa7}} denotes the weighting factor of the {{formula:27eee22c-5a78-4c14-9361-ee32fb3f7013}} -th user, {{formula:af4fb465-cc21-46ce-b4ea-7cb8b1a8a628}} , where {{formula:4fdbf210-d402-4fda-a945-c2fbbcebe014}} . Then, by exploiting the matrix derivative results in {{cite:47f... | r | 9253e4efafe3da8fb09140470d9fc1f6 |
paragraph41ex plus1ex minus.2ex-1emImplementation Details.
For a fair comparison, we follow the baselines to use a 32-layer (respectively, 18-layer) ResNet {{cite:c5618754c631847611c3f5858ed4c9ba2a90c119}} as the feature extractor for CIFAR-100 (respectively, ImageNet), and a fully connected layer as the linear classif... | r | 45d45bc8bc7ff430e7d80d641e8e9a15 |
The Expanded Wang-Landau (EWL) method {{cite:da153d9af33c5885d1c0bd827bc896c9d97ef386}}, {{cite:9f3f4b3e31c7baefe008604e04890fce5b2110ba}}, {{cite:3103715111c81b2af680a2103e90c66f40ec22a2}}, {{cite:2344ddc080e37d9281b92182765eaf25b3db0867}}, {{cite:0c9ddd98fad8faf4366306b33badcc13edabe6d5}} is a grand-canonical Monte C... | m | 5c0030369df72cb91d0eef59319040f8 |
It has been well realized in variational analysis that the subregularity properties (REF ) and (REF ) are equivalent to the following calmness and isolated calmness counterparts for inverse mappings; see, e.g., {{cite:a2e581a0ba2f1f9ba5e5a2dfb2a7cbd2dcc5080b}}, {{cite:227de480d6a7d26d8e4a27bdf89ea4d7cbe0e37e}}. Recall ... | d | fb49cabbf7fb0eb9498748d50d68ee05 |
To overcome the limitations of unknown sampling size and subspace dimensionality, the geodesic flow kernel (GFK) was proposed by Gong et al. {{cite:a7974642c4170712dc27c6d4abae1332278a95d3}}. They integrated all samples along the “geodesic" (the shortest distance between two points on the manifold), which is shown in t... | m | 823be0b84dee5bde123f30719771f52b |
The overall architecture of our method is illustrated in Fig. REF . Firstly, the input SAR image is fed as input of the ResNet-101 feature extraction backbone {{cite:9a1fe7bc1176415b0b4b7b966566ce5412f35f31}}, through which features of five different scales {{formula:596686bd-4acc-4c19-8888-7423a350310b}} are obtained... | m | be7e9922a5acd4c725a420152c5f94e6 |
Here, {{formula:ed6cefa6-b678-4d25-b80e-09ce049ac2cf}} is the discretisation error describing the discrepancy between the accurate forward model and the approximate model. The Bayesian approximation error method carries out an approximate marginalisation of the posterior over the error {{formula:0ce7ff80-51b5-4cf9-967... | m | cece2927491bb1003b52263ea5d90c06 |
The problem of finding the minimum number of fragments {{formula:718da555-8ec8-4747-b313-a51f51b40f6e}} representing
the Hamiltonian {{formula:11920503-3d0b-4e89-8834-b75f0b18faba}} has been shown to be equivalent to a Minimum
Clique Cover (MCC) problem for a graph representing the Hamiltonian. For this graph
each te... | m | 4f7b78496f5af23c2bc8ae40ffbfba7b |
We implemented 13 state-of-the-art methods, namely, Barlow Twins {{cite:fe29601180afb15311f35d7508555f78183482a9}}, BYOL {{cite:4dc6a39e1accab3708c1066675bf3da1d725f967}}, DeepCluster V2 {{cite:d2bbab22aad4bf113b091fb0b4eb46ac76b0d634}}, DINO {{cite:a2761055f0981734e7b4db882848b64e3af69e55}}, MoCo V2+ {{cite:60d83e06bf... | m | 948ee098a43a5601a19320c13dddbc77 |
The tools of fractal analysis provide a global description of the
heterogeneity of an object, such as its fractal dimension. This
approach is not adequate when the object may exhibit a
multifractal behavior. Multifractal analysis is a useful way to
systematically characterize the spatial heterogeneity of both
theoretic... | i | c5116dff89dd07271cf693115e03b6ef |
Task A: diagnosis of chest X-rays. We use NIH chest X-ray datasethttps://nihcc.app.box.com/v/ChestXray-NIHCC and DenseNet-49 as the classification model. This dataset consists of 112,120 X-ray images with disease labels from 30,805 unique patients {{cite:e4134be9e4b55fb971a4c5a6afe4e09354d25600}}. We filter out patient... | m | 2a64824be16b5e936bef7edf01d3793b |
Finger gaiting is an inherently difficult task for a robot. Given a robot hand, the individual serial link fingers must work in proper unison without collision; maintaining stability while making and breaking contact with the object {{cite:0c651284521ba2ccba8a02e2ef68222398133e7e}}. The computational complexity of this... | i | bca0133349345ec188fc7b44392a51ce |
The main outflow of M 3-38 is aligned along its bipolar axis and has expansion velocities up to {{formula:65bd69c0-54e3-473d-a0eb-1543e32b25f6}} 225 km s{{formula:27b94f01-562b-4e34-9e85-cec68aa6f7b0}} (Fig. REF and REF ).
This makes the outflow in M 3-38 one of the fastest among PNe, only surpassed by those in M 1-1... | d | 887227e555132c3d231b39e29d55c034 |
Most existing state-of-the-art object proposal methods mainly depend on bottom-up grouping and saliency cues to generate and rank proposals.
They commonly aim to generate class-agnostic proposals in a reasonable time consumption.
These object proposals methods have already been proven to achieve high recall performance... | i | d757e45ba1686c02f9579798728d9620 |
Uncertainty estimation in deep neural networks with different Bayesian approximations was shown to improve model predictions, either by explaining this within the loss function or by aggregating predictions from ensembles {{cite:0e175437791395bd2713d643069df891f331926f}}.
Such estimations have been successfully applied... | i | ff44ee5b0b6db79a505c1230e9dd6a99 |
In the following, we report the classification performance of the individual pipeline components as well as the overall pipeline in our experimental evaluation. We use the Matthew's correlation coefficient (MCC) {{cite:3b50c2a4220971b039be155f60924dfe0616905b}} as the main metric of our evaluation due to its clear adva... | r | 0f710799d8b22b95322e8759e877d7cd |
It would obviously be very interesting if we could directly observe the waterfall field(s) ({{formula:c94b763e-af12-46b8-8583-5fe426ff65d7}} ) via their mediation of primordial non-Gaussianity (NG), using the idea of “Cosmological Collider Physics” {{cite:b4aa4dbf70491b2735503bf2316c7adb291bb626}}, {{cite:879617ff8e92d... | d | 3ec4c94ffe1306cdc894b8c581140380 |
In this section, the proposed method is compared with the SOTA methods,
including unsupervised methods :ReDO {{cite:f4353e3d91b14deea154ea0008539263e2c33b46}} and CAC {{cite:dc17fd6baa95780e5e5821524bdc41658383a68e}},
few-shot methods: SG-One {{cite:75eeed652a59e1d86836776ed1a93f0f231be086}}, PANet {{cite:7117fc470589f... | m | e011bdb61f7a7dec5c2ecc388c557354 |
Two well-known architectures, PointNet++ {{cite:b16ebf7845f8e745def52886b59155d6418011f4}}, and MeshCNN {{cite:bc56182e786fed9e3e388b701439dfb19a251faf}} are adapted for the face segmentation task. To compare performance between multiple representations we use per-face classification accuracy and IoU as our primary eva... | m | aa6ebc2d7cb53c88389678a1e8696fac |
Recently, continuous-time models based on differential equations and their discrete counterparts have been attracting attention to deal with extremely long (and possibly irregularly sampled) time series data {{cite:391b2bddae23d817a25268ba8cd61e3fc3e98c27}}, {{cite:bf4fbe9066bcd40e24fe58cae039942a4026ee21}}, {{cite:00f... | d | 120a9f7a3f1d676c9fcc866645170a91 |
Before presenting our theoretical results, we briefly discuss about the available data from Au-Au collisions at {{formula:05e18a73-aa33-4125-bec0-31045fa0eaf9}} GeV on yield ratio based on Ref. {{cite:91ba5a4a775a439f9f4b2a66b93de42d5d6f98f2}} and Ref. {{cite:1daffa3a90f866013264de9ec60b32d37266b681}}. For {{formula:b... | r | f26099e5ac714e7e072727f947f6b9a6 |
Our results primarily hold for convolutional networks such as ResNet-50 and ResNet-101 (data not shown) applied to computer vision tasks such as CIFAR-10 (data not shown) and ImageNet . Can the same approach be applied to NLP? Many recent scaling law papers find a linear boundary based on single, full training runs, wh... | d | 3c2306cbc05f51ec22be234671e48011 |
Medical image registration aims to learn a spatial deformation that identifies the correspondence between a moving image and a fixed image, which is a fundamental step in many medical image analysis applications such as longitudinal studies, population modeling, and statistical atlases {{cite:e93def7603658550f0d8b9476a... | i | 16e0731226a98ac0f519966b118d4dda |
Better numerical optimizers. The judicious choice of the numerical optimizer is probably the most
important factor. {{cite:d3ebf2f1394c9e81491e878fa396cf5ed582e95a}} provide a very useful overview of
derivative-free methods. Based on their recommendations, the first
step is to select the best known derivative-free me... | d | 5bd05b28706dedb8c34c36856f4f5b10 |
with {{formula:381c111e-af73-4466-8ded-0a9a6ece52cd}} .
Since {{formula:709ad536-c18e-4175-89db-eda972f5272c}} is a polyhedral cone, it follows from Proposition 4.1.4 of {{cite:f8e55bb6c10abf6d69321b99f26ae338d7c372e0}} that there exist {{formula:0cb0271e-5582-43fb-a8b5-449236cb6521}} orthogonal projectors {{formula:... | r | f79fd1ed94d3380a48ad9f04f61062c3 |
Applying Theorem REF -REF to the graph {{formula:c434176e-66a9-46d2-abfe-5e319990b0de}} with the ECP, {{formula:03097a7f-4698-4dda-9390-f27ebe3c28c6}} , of Example REF , it
follows that its least eigenvalue {{formula:591b3108-9ec4-47ad-ae5f-9c72dc1fbbf2}} is not less than {{formula:30bd7b18-8d84-4bfa-b9d0-0717ca27e8... | r | f9badeb7b2507c52b131fcd128e7eb1c |
We present a generic optimization framework, called ModelMix, which iteratively builds an envelope of training trajectories through post-processing historical updates, and randomly aggregates those model states before applying gradient descent.
We provide rigorous convergence and privacy analysis for ModelMix, which e... | r | ee1bb52d62db0ebc7f3ea874bc740f9e |
Partition methods for long-tailed FL
To create different federated (distributed) datasets according to the different patterns of local and global data distribution, different datasets and sampling methods are required.
Data distributions in Type 1 could be realized by IID sampling on long-tailed datasets.
Similarly, Ty... | m | 88776699a0a9ae79de745999770927b9 |
As with any DML technique, our approach covers the following two major aspects of DML: 1. Constraint Mining: To appropriately mine constraints of examples (eg., pairs or triplets), and 2. DML Loss: An appropriate loss formulation to learn a metric using the mined constraints. In the recent years, a huge number of super... | i | 9ccd49f27e9e869682200ae2c6cd9616 |
We evaluated the anomaly segmentation performance between the proposed method and the existing SOTA methods mentioned in section 4.3.1 using the MVTec AD dataset. As shown in Table 1, the proposed method consistently outperformed all other existing methods evaluated in AUROC. The reconstruction-based methods such as {{... | r | 4e1386158f1f61b8ebe6f756ac14d4d3 |
Continuing to MIM, the advantages of HiViT become clearer.
With 800 epochs of MIM-based pre-training and 100 epochs of fine-tuning, HiViT-B reports {{formula:39646a7b-d071-4f29-b565-b04bd1acb710}} top-1 accuracy on ImageNet-1K, which is {{formula:a62cd601-8762-4792-b40a-dc67442220e8}} over ViT-B (using MAE {{cite:0b9... | i | 0eb1c1dd9e911214b58db062b9670ca4 |
In recent years, a new class of higher derivative theories has been discovered that is ghost-free and in four dimensions neither topological nor trivial known as Generalized Quasi-Topological Gravity {{cite:f51fdfdde18dffb6e68aeb8345574446ab198910}}-{{cite:e06acbb576444f695d10e766c6eb9ebd694f1ca7}}.
One of the such hig... | i | e7ea1a9cb2ed2fe82a3c5a313e32739a |
The encoder in EDNet is a VGG-16 {{cite:d8363c5ecde3b05f75e9b2e1032d12d741a4ccfd}} with the pre-trained weight on ImageNet {{cite:4b8a12f427b5353da7b6c6947a705e6262ba3391}},
which has five Convolutional Blocks (CB) and thirteen convolutional layers. Each CB's output is an input to the next CB through a pooling layer wi... | m | 7be1ef7d398dcfa78dfd1573f7794684 |
it leverages the functional oracles of the donor tests.
CraftDroid and AppTestMigrator explore a GUI model of the recipient app to find a sequence of events that maximize the semantic similarity with the events of the donor test.
They compute the semantic similarity of GUI events using word embedding {{cite:3a5bc58e323... | i | 53f6de3309484ec036a90cc6a64492a8 |
By Implicit Function Theorem, proved in {{cite:f7c2cc631b806565c90ed411ab786f58be62796e}} for the Heisenberg group and in {{cite:95303ee6620e32d852ee107ccde318cbdbd204db}} for a general Carnot group (see also Theorem 1.3, {{cite:ace7a89b4a590f2d4f78936dd1e92afb8a18bc17}}) it follows
{{formula:190cc4e4-ee05-46d9-b1b4-3c... | i | 9cdbb69790ee0a80bd0f24c051ab5cd6 |
Since our work is heavily based on the chiral representation, it should naturally admit a twistor description in the spirit of {{cite:8571897b6c6f637fbe09f7fa3fb3d6a0d3b226ff}}. To wit, it may offer a new perspective to flat holography, and more specifically higher-spin celestial holography {{cite:4b9798d6778e1f89ab3a1... | d | 255240f35cd269ca80dd33ebf160ce79 |
Extractive Question Answering is the task of extracting a span of text from a given context paragraph as the answer to a specified question. Question Answering is a task in natural language processing (NLP) that has seen considerable progress in recent years with applications in search engines, such as Google Search an... | i | 2656b041ae4d6f32b7317e5ef0970a87 |
We have mentioned that the smaller the widths of the intermediate exchange particles are, the sharper the peak of triangular singularity is.
However, through a detailed calculation, we find that if the widths of the intermediate particles in the loop are too small, some other problems may arise.
In the cases of this wo... | d | 0bc05552cd4776b85a63a036f7ca6a35 |
As concrete applications of our work, we feel that knowledge intensive tasks that involve access to external knowledge will benefit most from our analysis {{cite:596c13bb6a7134cffde5792139f839e930ecd281}}, {{cite:7e03f0ef007c4133d6cbc4e3cffd3ac8a774d3ad}}.
Additionally, Web tasks that rely on triplified knowledge like ... | d | 60405f7e362779c7fd4225ae1c9f92b6 |
Nonlinear isa provides us with a simple yet principled framework for learning speech representations in the presence of auxiliary variables, which in the case of sequential data like speech can be “time". Learning unsupervised representations can be posed as a problem of recovering from entangled samples the non-statio... | m | e5a28725a22c0ea7ae6595e6c73f94ca |
In fact, a standard coupling argument with site percolation on {{formula:26f88847-719f-46b2-a0c2-9a6e55d2a85a}} (see {{cite:8cbeb17c1a632f8df257456a881c72672b3d4695}}, {{cite:6f338dfdf87a1772578827bd27e9e852a5729fe1}}) shows that {{formula:d5172521-cacb-4293-833f-7cfe1da50ea4}} . In a similar way, for every {{formula:... | r | c47809f4b067ade58677b52304c66245 |
Here we evaluate the results in the table REF quantitatively. We couldn't compare out per class binary classification results with the MulT{{cite:32464d6745d4e758221a202f7f0054472b70e2b7}} model as they hadn't reported it, so it's unfair to claim that this model can outperform MulT on per class basis. We can still obs... | r | 19aca3aa065f3ef78d1a8eb0ca60d14e |
In this paper, we assume that we are given the data of a modular or super-modular fusion category {{cite:84146fe2ef414a7ecade23000dbf9e728da41f51}}, {{cite:ca64a4db19afe0db88cb9d8de63df6850764d805}}, {{cite:b5a6a6ba7a1ec17e9c92dc77b483c0b9f6de6ffc}} {{formula:ec314406-c384-4119-9bf2-992d3091d487}} in the bosonic or fe... | r | 16fa99eb0dc999ca75fb4ab8e2d626a8 |
Dynamical system view of deep learning has recently also gained a significant recognition {{cite:20d9150bb2fbd8577714928ab39ce6be9d5f45cb}}, {{cite:6bdab9547096545566ce3a7b4dacbd99fb6fb520}}, {{cite:221aee2924a8848ea4b9c92b37e31c4ad544f67f}}. Structure-preserving, in particular, Hamiltonian dynamics inspired neural net... | i | 58274c265c7fa62c2d2b423f750fb2d2 |
Two established methods for inferring causal relations between variable groups are multivariate LiNGaM {{cite:cbb94c3df0f846ceed8360717507d7bbaa338e9d}} {{cite:73d17798a50240d917ada605b72fafbcc8d3bffa}} and the trace method {{cite:326930bd95fa72604a9694ae02389df7d72b7e8c}} {{cite:d5144cb715610e18538eab6b1febbfa1ed27385... | m | 052abf7655cc5b9c37071701cb56424a |
While semantic segmentation based on deep learning has achieved remarkable progress {{cite:3e774688236ac6ba69efc43c8c6a8184810526cf}}, {{cite:61f962ae25affff34bfef54a39af6b804828b6d9}}, {{cite:fc4fc5482d51db1a62ad325f00be46dd60429990}}, {{cite:9bfb5183f99a54e39134aa3207de2687f58a12b8}}, it entails a large amount of mas... | i | c55258c37c23a82b1bcb339824669995 |
Variational autoencoders {{cite:0c8136bb22a366221a1af6c3edff68fafdd3272f}}, {{cite:7b33bd60be42ee5217a01fe502b29db8233d7d53}} (VAEs) use a neural network to parameterize a probability distribution.
VAEs consists of an encoder which parameterizes posterior probabilities and a decoder which parameterizes the reconstructi... | m | 93806df685098561d833a800577b3acc |
In 2010 we systematically studied decay properties of the {{formula:8d5c7940-9d3e-49c1-9022-fb0d6a707064}} ({{formula:2d900d2c-f5dc-4d0f-bb58-ef04756f93e0}} ) hybrid meson with {{formula:2059569e-7e23-40ed-b48c-53c4863700cd}} using the methods of QCD sum rules and light-cone sum rules, where we pointed out its {{form... | i | 3ec07389f3a781900306fad9f62979da |
Continual learning (CL) and its extension to lifelong learning, represents one of the most desired functions in an artificial intelligence system, representing the capability of learning new concepts while preserving the knowledge of past experiences {{cite:291f7ada4b8e28a5550cc946df19c1837826d5fb}}. Such an ability ca... | i | ae87026d6ae4c75a9b2ec9512f1ede6e |
Regarding the emergent symmetry, our results are supportive of the statement
that it is exact at large {{formula:fa65cbfc-a669-49e2-bd22-051fdb01d408}} , as we have illustrated in section , where we demonstrated its presence for an entire set of correlators involving composite operators in {{formula:913928c6-2b55-4821-... | d | 0ad886ee0c38f053bf82b7e8a60005f8 |
Several new physics constructions have been put forward to simultaneously explain the tensions in {{formula:a3ce0e38-9fdc-4f6b-b803-ffa0a3a5a961}} and {{formula:18ee366d-63ff-438f-bcfe-d9795218278d}} (see, for example, {{cite:d0894df5618efc4f3ab629adb13ce0f97cb0ced6}}, {{cite:906a7c1eb2996d2a45025951471e675703320faa}... | i | 821166b922a9bb653ab5787a1554490d |
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