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Within the category of graded manifolds, the most important seem to be the non-negatively graded manifolds. If the Grassmann parity of the coordinates coincides with the weight (mod 2), then we have a {{formula:1221ece6-04ff-4f09-b4d3-c6c2265c77d9}} -manifold (cf. {{cite:df09bb101395b91e8030276568b66bd56013b387}}, {{ci... | r | 59d6409a502d5c02ee4ba900dc0f357f |
RetinaNet {{cite:7f5bfdcbaf885008b244a501c1007aea8f4b134d}} takes into account the data driven property that allows the network to focus on “hard” samples for improved accuracy. The easy to adapt backbones for feature extraction at the beginning of the network provides the opportunity to experiment with deeper and vari... | m | 0f749c547ed9559962eb9caec473bf72 |
In this paper, three problems are discussed: the damping of primordial electric fields, electric solitons and their effects on acoustic oscillations.
As calculated in relevant cosmological monographs {{cite:19dbeaf5c63a4e1b510db7036f1db44f3e41f4a7}}, the effects on CMB from electromagnetic fields are often ignored,
alt... | d | 61df0a244ddcf69ea6ef2bd45a635040 |
NGC 5322 is also a core-depleted galaxy with a large deficit of stellar mass in the core {{cite:a664d52309fa10495d8f1c9cd7b113457daf985e}}. Such cores can result from dry mergers of galaxies. NGC 5322 lacks rich ISM as evidenced from non-detection of both molecular hydrogen {{cite:356fb1fbbb921561767e929d114b3e173cb3fb... | d | d8ab9f95bd72a75da43dbf2cf9f5f261 |
However, there are many limitations of this work.
First, the nonparametric framework analyzes properties of the empirical risk minimizer, e.g., convergence rate, sample complexity, etc., but doesn't provide guidance to practical optimization and how to find them.
Second, the proposed localized separation condition, lik... | d | b3dbccb4305500d14f194bff2c4ebebc |
The idea of using a subset of the matched asymptotic equations (constraint equations) to learn about the backreacted description of a brane configuration in some background lies at the “soul” of the blackfold approach. In the blackfold approach, the constraint equations, which are dubbed blackfold equations, provide a ... | i | aa8edaf234cbf0068104899e8c405149 |
For Eq. (5), we utilize the D3Q15 lattice structure {{cite:f2ecaafacbec3d89861f276967cd4cdbbc1829ed}}, where the weight coefficient is given by {{formula:41ae9053-1b1e-492d-bd78-5f06bf804531}} , {{formula:041a07ba-86bf-44ca-918f-722a38666b57}} , {{formula:70984eb6-ea6d-446b-813a-fdb3978d6cce}} , {{formula:c7f6e5b0-41c6... | m | 004a7f776ea2a4ecb497e7be8d13998f |
From the perspective of the user-item interaction graph, the individual interaction history is equivalent to the first-order connectivity of the user. Thus, a natural extension is to mine the higher-order connectivity from the user-item graph structure. For example, the second-order connectivity of a user consists of s... | m | 50c16578259b77527689f17729f46f6f |
By going back to the original analogy with genes put forward by Richard Dawkins {{cite:4d7508c555371cf8913661b381410e7665bb3fce}}, we investigated the relation between the occurrence frequency of scientific memes and the degree to which they propagate along the citation graph. We found that scientific memes are indeed ... | d | 04107b700ea39e154c81b49697581879 |
Influence of backbone networks. Besides the simple Conv-64F, we also use other deeper feature extractors to evaluate our model, i.e., ResNet12 and WRN-28-10. We compared other state-of-the-art methods that using these deeper feature extractors, including Dynamic-Net {{cite:fb34d8978bb4c333d8f6870f74c497ffbe6e61d6}}, SN... | d | 16fce1975ee9ebd0e346f968f32f14bf |
Despite its similarity to standard ODQA tasksHistorically, open-domain QA meant “QA on any domain/topic”. More recently, the term has been restricted to “retrieval on a large pile of corpus” {{cite:99a741aaa3c42f9e51b42c2cd53bb99b1e8a0783}}, so “open-retrieval QA” seems a better term here. However, to follow the recent... | i | 96cd3111088f22c9b926d8be0053cb4d |
An important feature of convolutional networks is their equivariance (consistency) with respect to the symmetry transformations of the input data {{cite:83ee2cd2fd2b19e9f867d4cc1d1a6700aae05053}}, {{cite:40ac02a5268a1c49292e585a183f971aaea4eb4c}}. Equivariance guarantees that exactly the same filters are applied to eac... | i | 00dc99588ff0887dfc901891fea88ddb |
Table REF lists the comparison between the proposed HSTGCNN model and the latest state-of-the-art methods using ROC AUC. The ten methods are Frame-Pred {{cite:72afaa1150ce8dd772c1872be33e0ae14aba41a0}}, MPED-RNN {{cite:2bb8e7bdf7f83a9a0b28b1d5a742473c8aae6649}}, w/Mem {{cite:f6c8239c998ba6855b8a1d1be0d4a2fabb23a572}},... | m | 3e69e259f7775e87eb6e4758ff31cf8d |
With the increasing possibility of Urban Air Mobility (UAM) in the recent future, quadrotors' need to navigate through urban high-rises becomes increasingly inevitable. Monocular vision continues to be a widespread perception modality for quadrotors considering payload, portability, and endurance. Hence navigation bas... | i | 111084b5d8e671d3a230cd5e4b40382f |
In Table REF , we have summarized the contributions
of stochastic GWs to the fluxes of flavor neutrinos at the Earth.
They are at the level of a few percent. The current neutrino telescopes
are able to detect up to several thousand neutrinos from SN in our
Galaxy {{cite:a7600e6a70cfa9d1f2878acd4495efe3ddfbe443}}. Futur... | d | 15ec623c37e2ddda2fc7a6b8c5e6bd7e |
Mathematical modeling allows us to analyze various natural phenomena and find optimal solutions. Two pioneers in this area, Kuramoto {{cite:1dd17086a25d86b932739a5380279da65906832c}}, {{cite:d7622f6a9413a6b1eeb15808b23481554925bc48}} and Winfree {{cite:161fbd9cae928e05693eebf94c860eade4915180}}, catalyzed studying math... | i | 4ff43974b3d1137e409b887b681e8799 |
Deep Convolutional Neural Networks (dcnns) have proved to be useful in highly complex computer vision tasks to identify visually distinguished features of images. The effectiveness of dcnns are also being explored in recent years in document object analysis by various research groups {{cite:71d2112241ff2db861e5d508e9fc... | m | de3a3938ce7561c9647148a6d1533484 |
where {{formula:5784e335-6b58-4b05-a8e6-33fe800a515b}} is an inter-UAV attractive/repulsive term, {{formula:09b214ec-3e4c-49aa-b6b2-f13064b04c8c}} is a velocity consensus term, {{formula:ac71e68c-5a7a-418c-b6cc-e64ada77bb1f}} is a term defining the individual goal of each UAV. In order to create smooth incentive fun... | m | 1fe1e5a55ad3147745160d5ee71fbd67 |
The first consequence follows from the fact that the scalar field {{formula:914ec7a9-eee2-4b18-9b17-52f1aa3d02fc}} is only an {{formula:2ea9afb8-8dc1-4d02-b03e-a0601236c208}} valued for {{formula:2ede8350-3a84-4487-b95b-e152f99ab286}} . To have a global covariant topological current, the scalar field {{formula:50cc66... | i | ff61019d86b239e6c203d2de2c5d5155 |
We additionally compare our method to Wang et al. {{cite:c9c05cf15b941b1c9193ac4ba5f5b11c2c332d74}} who proposed a recent method for multi-person pose forecasting achieving state-of-the-art results on several datasets, as well as other recent methods including HRI {{cite:dc69880c581407dade5281577bebca0c043103a5}} and L... | r | 582d9face6c1d2f376269010b07882b3 |
To simplify notations we shall derive the spectral method in the classical Fourier-Galerkin setting introduced in {{cite:112e13a9e7afa3f60a8863cae221b59e971c7cec}}, similarly it can be extended to the representation used in {{cite:8b47718156beb3bb5f4e8c14436b48e953515833}} for the derivation of fast algorithms. Thus, w... | m | 28a848d071bc4856f4dc3356e3793bf1 |
Datasets & Metrics: We evaluate iFS-RCNN on the modified version of the COCO 2014 dataset {{cite:4f086a174d77a5deb4e2cf786f66d1824ff41a7c}} introduced by {{cite:cbd0656fe263a08de67665cd6484fa4b3b193113}} for FSIS and FSOD. Also, we are the first to evaluate iFSOD, FSIS, and iFSIS on a new split of the LVIS dataset {{ci... | r | 3a86bf7a73218edb3b25295967b2561a |
Our method also generalize to NeRF models. We use PlenOctrees {{cite:67d031adf904fda256bcbdb1441c01b8912aaab0}} to extract the discrete volumetric representation from learned NeRF networks. For our purpose, we use the NeRF-real360 dataset which contains 2 real-world 360 scenes. Following PlenOctrees {{cite:67d031adf904... | r | 99aa09fb05fcae217397f7ea78254583 |
Solutions of (REF ) in the whole space and evolving from initial data {{formula:a5097ddb-8e04-462b-9af4-d0b31d2e1136}} become bounded instantaneously. This is captured by the famous Nash estimate {{cite:8164fd7b470995bde518fafdeb090491e58d0e38}}:
{{formula:1bd49957-3f54-4fad-be05-5cb3e9d7dc12}}
| d | 3c68b61ff3056fd1dbbec7136619ae94 |
We present the numerical solutions to the BEs as shown
in ıineq:BEN,eq:BEL() for the benchmark model defined by the
rescaled Yukawa matrix presented in ıineq:rescaledyukawa(REF ), and for
a tri-resonant singlet neutrino spectrum. In the following analysis,
we restrict ourselves to heavy neutrino masses above {{formula:... | r | 8d973765a15880801d04b7348a81a384 |
We compare with a recent bayesian continual learing method, CN-DPM {{cite:6850aec5dd1660c6e4783133618473d1d84784b8}}, for completeness of our work. We report the results in Tab REF . As shown in the table, CN-DPM performs better than MERLIN on Split-MNIST, but drastically fails on harder datasets. We note that the base... | m | 07d997b7d7603f52985d4891761fee18 |
It should be noted, however, that our findings need to be considered in context. We evaluated one particular type of CSA – a chat/text based CSA like those proposed in {{cite:da917d746ab1dca40341c163857a522e9c911b83}}, , {{cite:f339623b3c4e0a4b9aa8579cdeb47933ee69add0}} – where we employed the traditional IR evaluation... | d | f09318bb921988d1eed73743a61eafc7 |
First, the SIF method which had been shown to be a robust, flexible, easy to use and yet competitive state-of-the-art baseline by {{cite:a7bcdb56f24d90ed09862b3882b7440ad07055b6}}, has also been confirmed for our technical and scientific domain. Unsupervised general language word embeddings, while not optimized for the... | d | a30e1e19e665474d2a534b1314b4b079 |
Once the isofrequency contours of the infinitely periodic structure are obtained, these can be used to infer the behaviour of a finite laminate, given a large enough number of bilayers are taken{{cite:8be28fe0ebc5e530922bd05997c0e4f4ca9e2dcf}}. The design of the corrugation for a particular effect then rests on interpr... | m | 1f4176602475bf30d9630bbe207fc661 |
where {{formula:8214597b-29bd-4234-a057-ebed93874b5b}} is the {{formula:00d437ac-c628-472c-821d-62c2e31e7fc7}} 'th k-quantile of {{formula:fcd9aca0-666f-4ee1-9cf9-e2666aaf9cca}} and {{formula:aab289e6-d697-482a-9ed1-bbdb79f5c15b}} As a consequence of Proposition REF , by conditioning on the estimated propensity sco... | m | 6198d5ccac306180912ab866e9b4226e |
The presence of very young stellar populations in the environment is often interpreted as the SNe having very massive progenitors with similarly young ages (e.g. WR stars). However, it should be cautioned that the SN progenitors may actually be much older and reside just in chance alignment. Also note that star formati... | r | d36c0da0988a9e8b77209b0188361115 |
We analyze the I{{formula:b3efc52d-0881-4fe5-b73c-16bb47146cb9}} CDM and {{formula:d8684767-e3fa-41dd-97d1-c6a716c915f7}} I{{formula:41e68b2d-76ba-482e-a8b4-1daf3b92bea0}} CDM models in contrast with their respective counterparts {{formula:58166ff4-c421-4f1b-8960-a7c19b429ad3}} CDM and {{formula:4cd6c92b-1ec7-4b60-bb88... | d | 232b579bc91a43a6a9202b6495e2cf88 |
The interpretation of data from stellar observations requires a stellar model to compare against. Traditionally, these models have been 1D global models {{cite:11167d469f65f6ee2f49c06385a488497acd72b6}} that use formulations of mixing-length theory (MLT) {{cite:77274f4e0cf0c96e93849825a45cd7f12619dbe4}}. Later models a... | i | 96ed55ae8aa1c1b395c52aba09cff28b |
One research line is to formulate the drug generation problem as a sequence generation problem.
Most of these methods are based on the simplified molecular-input line-entry system (SMILES), a line notation describing the molecular structure using short ASCII strings {{cite:42f59a2b9bf1ce47b0a5f24d08b35e745deebaba}}.
| m | b51844002604ccc8dca73d6457b3d7a1 |
In relation to the neutron star properties and the astrophysical constraint, one of the most robust constraint is the minimum mass that a EoS must reproduce due to observational measures of massive stars via Shapiro delay.
Not long ago, the neutron star king was the PSR J0348+0432, with a mass of 2.01 {{formula:0b0f711... | r | c2b06631d7960903287d69c38167dafd |
The latter can be done using existing interval methods that compute interval enclosures
for the united solution sets to interval linear systems, see {{cite:78dd339a0d6cecc51f0f99074636682e2a0acc37}}, {{cite:a244686589d3af403f0df2daf56aa18ca8a3f1ee}}, {{cite:f27fdcb1cf1dac137fdcd341c5076d1d0daaba5a}}, {{cite:124e2c75915... | m | a96da082ac30d77a4a6296ed26eb48ae |
The task of Automatic Speech Recognition (ASR) involves building systems that can transcribe spoken utterances in isolation. One major problem with building efficient ASR systems is that they are data-hungry {{cite:6a3bded89860f6779b89de5eb404a5ab2ccdda6b}} and with the introduction of deep learning to build ASR system... | i | b25a8d3f7b0ddd3649e1c60e6ab2a949 |
Ethical considerations. Since GST generates the visually-grounded dialogs, our proposed models have the potential to produce biased and offensive language, although arguably to a lesser extent than the open-domain dialog {{cite:e56309519f02307c1743fc7afa54e60d5b666602}}, {{cite:f2b8bb88fa98bdb24a2acc3fba583dbec5fc19c6}... | d | 27c6e323db110ca56936df2b93e892be |
We begin by briefly summarizing the mathematical results we make use of in the paper. For a full discussion, of the Resolvent/Green's function method in RMT we urge the reader to consult one of the many excellent reviews or textbooks in the field {{cite:f7c381d9d2514365ff77812b969a0284335c9371}}, {{cite:bb31fd86afb66e3... | m | fb4946bdd38bff7d4845d6873b93b875 |
In the same way as a number of projection methods of feature extraction (e.g.
Projection Pursuit {{cite:1d5ab68e902816d7e8567ca4c2b0fa7c5f3cae27}}, Partial Least Square Regression
{{cite:43a17c0ea3a44a731ba2d95ea78da6a422b806a1}}, {{cite:b8883910636576a8178f35cf9963c82b8742980b}}, Conditional Minimum Average Variance E... | i | 36ad177b062b6e3142c27533f6e734d0 |
A variety of models have also extended beyond continuous/binary models for the mediator and outcome. These include models for zero-inflated count, survival, and ordinal data, as well as quantile regression models {{cite:acf2aa3f9c564c5e1d3cef559d0d9db02aa47d10}}, {{cite:09220b1bc6b114ef91b432cf4b14fb5f68593f56}}, {{cit... | m | 2661bbf8567802cf52768e6f7b543f0f |
with Dirac delta initial data {{formula:47f31232-981d-4076-a432-a6dada0785be}} Here {{formula:c69f4314-de99-4447-bda2-e27a92f70896}} is the space-time white noise. The SHE itself enjoys a well-developed solution theory based on Itô integral and chaos expansion {{cite:704888af46f2de420ae2c42209579ce3b67eaa86}}, {{cit... | r | 5843c698f7d425e3cd74234f437d7529 |
The first method given in Ref. {{cite:43d0162340092dce230ee136744fc36349eea399}} is based on semidefinite programming (SDP) {{cite:809a6b0f417c46c077a8a352fc73a087e4b5110b}}. One starts with an antisymmetric state {{formula:f3cdb6aa-55d5-48ca-9ad5-cbbeb5a7284b}} . Then the task is to find the PPT state {{formula:f3c29c... | m | f5f10c87cb76624631ca4a0c4a2572ed |
To close this work, let us give some comments about this project.
Due to the axion, the quark potential and entanglement entropy is
shifted as some holographic study in four-dimensional QCD with an
axion e.g. {{cite:05a701b5da58d18be307406b0eca1600ea65e7d2}}, {{cite:d836637f10e7fcf6edbe3b9775c4d28adcc1575b}}. However o... | d | 4c2531a05afaf4db2132e0a1d8a6459f |
Densification of wireless network is a promising future direction to satisfy the explosive mobile data traffic demand.
In response to an increasing demand for data traffic along with the use of mmWave and terahertz bands, ultra-dense network (UDN) where a large number of small cells are densely deployed on top of macro... | i | de6bb18002d48ed68151a1cc55b5f462 |
Recall that for arbitrary matrices {{formula:c109a386-cc5d-407f-a750-e09d2aeabc24}} and {{formula:a70e6bd6-d65d-433a-aabb-3160c58db9e9}} it holds {{formula:3e9a5b6e-854c-4f4f-b625-d6e0204a93cd}} {{cite:dc9c2dc8434443633512dc4a01a95098f9124329}}. This together with the Hölder inequality with (3/4 + 1/4 = 1) and Lemma... | r | c7c25653f5994e93eb85e23d02d7b308 |
More practical approaches in this regard have involved novel changes to the optimization procedure itself. These include adding a “momentum" term to the update rule {{cite:6decd7ff659ec8f6f11dbc3f4fff86afbd7e7a46}}, and “adaptive gradient" methods such as RMSProp{{cite:3ac8f9bbb2ae004e6ad87dc79457df039a24ef85}}, and Ad... | i | 4486600b0a568e4f238b04b812e51c16 |
where {{formula:4f88236b-adfc-4709-9fc6-501fc693d549}} and {{formula:50d6e002-5ccf-4604-994c-aa44d97eb6b8}} for all {{formula:57c86e96-4050-43a7-9513-2545335cb1cb}} and {{formula:e482b8d8-d798-4b38-8a80-e8746eebddfb}} . Since under Assumption REF {{formula:cc36caa9-a8cf-447e-8fd1-c092bced36be}} is assumed to be st... | m | 84cbbfc7a48bfbdc3dc15b7f37290725 |
Moreover, our method significantly outperforms previous methods on the precision item, which attributes to the false-positive filtering strategy.
In the end-to-end case, our method significantly surpasses the best-reported results {{cite:3e1153ca47216aa4f2c8cb188bfcee29112d13d2}} by 15.7% on `None' and the best of resu... | r | eb684448bc7615eff8c8124c0557ed48 |
The goal of this work is to propose a conceptually minimal combined contrastive masked autoencoder approach, aiming to find better trade-offs between simplicity, efficiency, and performance. Consequently, we choose to omit a number of commonly used self-supervised learning design components. For instance, we do not use... | d | e068b69eb21b75b22f8b87d34856591c |
We have applied the LCO formalism to a new loop order for any theory and in
particular a gauge theory. Our main focus has centred on QCD with {{formula:4ee86062-9e9e-48bc-be9a-986999179b49}}
massless quarks. The key observation is that for Yang-Mills theory the three
loop corrections to the effective gluon mass derive... | d | 176ee47d5abdfe7d1ffbe487b745a5b7 |
Finsler geometry as a more general geometry could provide new sight on modern physics. It is of great interest for physicists to investigated the violation of Lorentz symmetry {{cite:8b4b3ec4823473b3affcf1efe50be7f5b8dec230}}. An interesting case of Lorentz violation, which was proposed by Cohen and Glashow{{cite:0a96c... | i | 0d334dd1a55225d1d62b32ae93f5fc5e |
Limitations and Future Work
There are two potential improvements of GroupViT to explore in the future.
Firstly, GroupViT's performance is lower on PASCAL Context versus PASCAL VOC. This happens due to the presence of background classes, e.g., ground and road in PASCAL Context, which are less likely to be labeled in tex... | d | 71fd4a229351d5a8286111a45eed93ce |
We recall from Chapter I of {{cite:d5b1659709259d9fce60cc57fc908f3a078a1c6d}}, that a closed subspace {{formula:72d86b3f-07e3-4557-a8b3-5688d144b8a6}} is said to be a {{formula:012d0b89-781c-4f95-8098-3a5ce1058c99}} -ideal, if there is a linear projection {{formula:3a936e68-b4fe-4263-8885-c6d419b50b3f}} such that {{f... | i | bf3ffb9c49dd605463b50e9b470c2a18 |
In {{cite:3168d05dc42ee11355462d4715542bc600da169e}}, the reverse perspective network is applied for object counting to solve the problem of input image scale variation. The perspective estimator can calculate the perspective parameter and the coordinate transformer can convert the images to similar size. The weight of... | m | 22cfe13dd0d620604880454930a64099 |
As far as the non-thermalization of other observables
than the energy density in (REF ) is concerned, obtaining rigorous
statements turns out
to be rather difficult, while non-rigorous
arguments are straightforward and still quite convincing:
For simplicity, let us focus on observables {{formula:725a6051-97ca-4f39-8b77... | d | 5faa9447f6eb11aa6d4f4794b65099f9 |
Lemma 1 ({{cite:21ed186f0cc0f6b06da46cbd3b7f29f6b82e99b6}}, {{cite:a8f80336cdfad87b7349df07d89244bc421f6707}}, {{cite:61d7eaeb0293b577491c34c114920bebfbf670af}}, {{cite:205afe9ebeb140970394bc5643201591f9ba5ec3}})
The connection matrix {{formula:b0ff07a0-16f1-4b9f-b990-361f9be97aec}} of {{formula:4ba708d0-5c09-4180-bb... | r | a9eb8f031d90525eaff1a9b66b4ea78a |
The overall pipeline of the proposed model is illustrated in Figure REF . An input image is first fed into a pretrained ImageNet classifier to extract its image feature and a probability distribution {{formula:b8141ba8-01da-4da5-a32b-ed15946466a4}} over the ImageNet classes {{formula:f986faf7-c2df-4d2a-9954-4c525c3ef... | m | 4d3df5a93ce76e8d785dafd6be226a76 |
1) IRTK: One of early image registration tool for breast MRI images using voxelized mutual information similarity and free-form deformation model {{cite:340e8a20e74df1dd4da86cd4a22bd955b8f87374}} . Before starting registration IRTK apply contrast enhancement to make similarity measure insensitive to intensity change. A... | m | 34b982c674a4e6219a6af62a65f96a1b |
Table REF presents results using pre-trained BERT features.
We extracted features from the pooled output of final transformer block as these were shown to be working well for most of the tasks {{cite:cef36d9f67d4ef6db85477899b6b1d764ecc51e9}}.
The features extracted from a pre-trained BERT model without any fine-tunin... | r | 89d4a194657c86022d92b42f20dd227c |
As mentioned earlier, we perform our training with 924 seen tags and testing with 81 unseen tags for zero-shot settings. However, in conventional tagging case, all tags are considered as seen. Therefore, we use the 81 tag set in both training and testing. Note that, in all of our experiments the same test images are us... | r | 51661e59319a5281222b9c2297fb663a |
First, general features extracted by 2D CNN in regular pixel grids with fixed receptive fields often have difficulties in handling thin structures or textureless surfaces, which limits the robustness and completeness of 3D reconstruction.
Recent MVSNet-based attempts {{cite:513096d334333af58347573614bdce9ffc5c6a15}}, {... | i | f3f4ec8853d96f5d6a62446f9786a742 |
Results and comparison: The results in Fig. REF and Fig. REF reveal that our method creates better contrast with lower noise than CycleGAN, and that contextual information from region patches assists the formation of local information (e.g. the lizard head appears much more clearly in our result). We also provide com... | d | 3752f917c9202a333463b30f5f099613 |
In constructing the linear model of epochwise double descent, we assumed the existence of small scale (small eigenvalue) features that are largely unaffected by the presence of noise, and learn slowly compared to to larger scale (large eigenvalue) features which are noisy. Near critical parameterization, this gives ris... | d | 02dd1d93054e85ed07a145e5c27d7107 |
This work uses the global gaussian interpolation, Gaussian Process Regression (Kriging) {{cite:d0772b829d2c453c411b7ae209b257f22d1a2d20}}, support vector regression {{cite:af86f5ecbd4d0d1934bf71ee4b366a1668a998b6}}, polynominal regression {{cite:7f2b54f582c2904ce188ce6f397fb21cf983350b}}, neural networks (NN) {{cite:62... | m | e9aaf6eb3e579418375901f27ad8dc05 |
Mesh-Based Approaches. Given a monocular or multi-view video, earlier methods reconstruct the detailed geometry and textures using parametric mesh fitting {{cite:2ced7d349f02aae7bb9dd74cd08c7abd34aa5018}}, {{cite:7a6f5786f8a90c0ae7f2ea23ccc7de89058d6864}}, {{cite:9cb2e48ed2b137df52b21bf12d02092f1cd8ea61}}, {{cite:3f149... | m | db04b43814d60ffb5c5ed66a94433ed3 |
From another perspective, we take OfficeHome as an example to visualize the effect of the adversarial training in Fig. REF . Specifically, we train vanilla ERM models (without prediction disagreement-based adversarial training) and ERM-based AdaODM models (with prediction disagreement-based adversarial training). Then ... | m | 7c36e18ecc9a509a150b8d9164c24e69 |
Hom-algebras and Hom-coalgebras were introduced by Makhlouf and Silvestrov in
{{cite:72246016fd127845e057e261b05931cf2b6d60b4}} as generalizations of ordinary algebras and coalgebras in the following sense: the
associativity of the multiplication is replaced by the Hom-associativity and similar for
Hom-coassociativity.... | i | 80402bc66c0a39e5568208782a2612f1 |
the first nonlinear evolution PDE solved in 1967 by Gardner, Greene, Kruskal,
and Miura {{cite:190d2f3f7f92b9275950d4a6c5cc15e10207ae97}} by the inverse scattering transform (IST). For
the reader's convenience and to fix our notation we review the necessary
material following {{cite:b1b9a3130a8f1a94012efc0a56c6b24ee7c5... | m | 859190d524dd7fe0becf374406319368 |
In RL, the agent is not being told new knowledge about the environment and what the correct behavior should be. The agent learns new knowledge indirectly by guidance of the environment. Moreover, this guidance is simplified into reward rather than knowledge itself. But as long as learning the limited new knowledge dire... | m | fd3fc87a794c4ee954a601075a083cf1 |
where {{formula:0623123e-2ed5-42a8-bcb7-3701593ce1a8}} is the cross section for {{formula:370fd1d1-09c4-4e14-8f72-b7e502f08ef1}} annihilation, {{formula:a753f3c0-98dc-48b3-b27f-82a11f824c78}} is the flux of soft photons in the observer's frame and {{formula:46fa426a-a04d-4315-a263-b1ebef5c21a6}} is the luminosity d... | d | e2bc896749cd8edc891d4a60edd7f385 |
Given a cosmological model, eqs. (8) and (9) can be used to predict X-ray fluxes of quasars at known redshift. We compare these predicted fluxes with observations by using the likelihood function {{cite:0edeb3e0a02ea6491cdbe34f21843bb3e75669a1}}
{{formula:4b1575a6-6b90-4a42-b94b-8d467af046c7}}
| m | 42ac5a8e80c12f6076c06d7ad60cf910 |
The 3th order formalism of the WKB approximation presented in the paper {{cite:ddf77040acbed24a2292b3a2ca85bb31f8cbcbb0}} has formula
{{formula:132a752e-3261-4a31-9e1f-1d5fcaa6e0f1}}
| m | 607635a773aae21f0839ce02d45e1fd4 |
In the search for the CP-violation in the leptonic sector, crucial information has been obtained from reactor and accelerator experiments {{cite:9e96d64eb154f343ade17269198e9839a01638d0}}, {{cite:9c6c65c9476f2ad782f00ba9574fcc3f3e14e64d}}. The discovery and measurement of the third neutrino mixing angle, {{formula:9332... | i | f4d5933543a9dbd37f04f69298b469f6 |
In Ref {{cite:5658cde4b1f9789529ad75d048d8633cec3e742a}}, the S-wave tetraquark states with all quark configurations are systematically studied in a non-relativistic quark model. The parameters are fitted by reproducing all S-wave and P-wave ground state mesons. The charmonium-like tetraquark states {{formula:0d09d317-... | r | 0acbe3e7446a80320d11c67a971ea1e9 |
Let us first look at some examples. Since in a complete graph every vertex subset is a general position set, A wins the {{formula:c31b39a1-2843-41cf-937b-28976d2aeef7}} -avoidance game on the complete graph {{formula:88f1e350-5bc8-4f95-a0bb-ad0d9d0b450f}} (and loses the {{formula:97bef430-c7c5-4839-8fd0-bf8f80ae2eb2}} ... | r | 487dd0eb148235c0052b5289bb754aa7 |
Sketches Generated by VASkeGAN:
We allow the trained model to generate sketches after being conditioned by a sketch from a particular class. A sample of the generated images are shown in Figure REF . This confirms that the model is indeed generating meaningful sketches and not random strokes. Here too, it is very clear... | r | b1955e7e76b61107332ccd25545a32ab |
Next, we give an overview of our approach.
For any given query point {{formula:0d03ca03-a8ac-4f11-ba76-7244fdb6eb68}} , we compute two binary trees (called visibility trees) to store the visibility polygon of {{formula:abb4182e-b815-4c60-818f-85fe608327df}} .
These visibility tree data structures in our algorithm are a... | r | 900c98f8b7c1ef0d922c52c520ab6f9d |
Auxiliary variable approach. The proposed schemes are based on a reformulation of the time fractional Allen-Cahn equation
by introducing an auxiliary variable — an approach intensively studied recently for gradient
flows; see, e.g., {{cite:a665ced9d4dd6a4910704e0dbf5060e5dc1a27e2}}, {{cite:a3261249344703d7074860ea8c6e5... | m | c75c9e402f23a9d5f23b7d33b172f77a |
where {{formula:e57589ff-b27f-4261-b0ad-a120f770cb71}} is a flat measure, the standard deviation {{formula:9c1bec36-fb2f-44d6-89bb-ddf0a333db14}} sets the energy units (and was set to 1 in the numerics), and {{formula:92e74d3c-4647-4a0f-8c46-22dab6dc4f4b}} is a complex hermitian or a real symmetric matrix depending ... | r | 0ca9b8a0f29309598443e80340b9d27d |
We have several observations from the Monte Carlo numerical experiment.
As shown in Figure REF , all methods are outperformed by the proposed identification scheme, which maximally incorporates the internal positivity side-information.
Indeed, the side-information helps excluding spurious model candidates and subsequen... | d | e13ba92c1f985a6adaca73feb216847d |
The unpolarized and polarized non–singlet and singlet anomalous dimensions have been calculated at one–
{{cite:e89665dc21df55ca3d359956d08b9fc772426ee3}}, two– {{cite:25d69d42f32fc71b1975768945c9ad55f5ab5855}}, {{cite:d3a59ab683ea2dd2a0e58e2dfd64e4f9ac802f3d}}, {{cite:e02ffc019935c5fc05c23c2e8962c9ff587e0ac8}}, and thr... | i | 62362e7cfe37d5fe111aaac26a55c99b |
tocsectionReferences
Appendix
Robust Central Path
The goal of this section is to analyze robust central path. We provide an outline in Section REF . In Section REF , we bound the changes in {{formula:fbf2ee60-f696-4ca1-869d-f9f71ca2e2b2}} and {{formula:fa935e72-1fbd-4788-b018-6532b0c02ebe}} . In Section REF , we an... | m | 6dc9397ad25227fed6dbbfc4f0433581 |
Use of thermal infrared (TIR) cameras have always been a popular research topic in ADAS to improve night-time driving by enhancing driver’s perception. Also, infrared cameras have the advantage that they do not sense the illumination conditions, but the thermal radiations instead. Their robustness to illumination chang... | i | c8d3cd45e8679bcc7a755999b3706d9f |
In our experiment of the Poisson equation, where we can directly compare to traditional PINNs, we observe that is possible to obtain similar levels of errors, showing that our method can also be used for simple domains. Furthermore, we did not see a decrease in performance when we compared the numerically obtained eige... | d | 83e5ad2a3dd1d8356496cf98d7bcb178 |
AAS can be applied to other tasks, for example, machine translation. BLEU{{cite:ebff67931a3cd799dbd4c5427456db3ec59192cd}} score used to evaluate machine translation models incorporates an average of n-gram precision but does not consider the synonymy.
Therefore, METEOR {{cite:15b20b6eb73ed18c921a0f39529dbc8b00aa31f3}}... | d | 1019a1a031e56792ae09e8e92aba8be7 |
SAC. For single-agent game, soft actor-critic (SAC) {{cite:00f83862adc7a427bb03a456a31adefcd61d06f6}} follows the maximum entropy reinforcement learning framework, which optimises the objective {{formula:f15c9b09-2c13-4aa2-a0e8-b0de4cdeda77}} to encourage the exploration {{formula:371ca24f-1adc-40f4-8973-834a117057af}... | m | 6719a1d5748cbdae909e3e9405a69042 |
Limitations include common parameter estimation challenges when the number of model parameters and/or variables increases relative to the variables or quantities of interest for which data is available, as well as the lack of known nominal values for some model parameters in large pulmonary arteries. One challenge is n... | d | 7a7616838b5373e38f3f6ffc3a8d656b |
Note that the DC conductivity characterises static low frequency fluctuations of the system. Recently,
the butterfly velocity {{cite:baf1d004e22742b4c294f4e3986db40e610ed75a}}, {{cite:ca84f8934d508ba514ffc9b69b7555ec7d7319ef}}, that shows how fast
fluctuations propagate in the plasma, has been studied in holographic an... | d | 97bf69f9651537a28a19038cfd1aa601 |
Modern successes of deep reinforcement learning (RL) have shown promising results for control problems {{cite:d50e503a0a8c3be21445f8d0d9fee40400679a1f}}, {{cite:87d9e1b49f62833b353282120e1afd2907f3170d}}, {{cite:6915c0b59ca8ed3371b5fc2e7b22a6f98ee5f14f}}. However, training an agent for each task individually requires a... | i | 19a6f11bac8985e2a2fab525c7f768c6 |
The aim of this paper is not to propose a new architecture with high image segmentation performance, but to investigate how different augmentation techniques affect the network's learning. Our results show that data augmentation significantly improves the performance on the validation data in many cases compared to onl... | d | 97bfeb7c57904a409eef0447be01fb45 |
The second step consists in looking for the extremal normalized sums of uncertainties with respect
to the involved parameters {{formula:6987412e-f788-47a4-8356-fc9d31627710}} . We start with the necessary conditions
of separability (REF ). Although not exploited analytically for {{formula:508add4d-4e68-4c17-933b-832073... | d | 8bdd9659db6dfd5b4186a1f114f7654b |
ENet is the following regularized least squares model {{cite:2e20db6405ca9e6b798a9bf2353d168be1ae3b9e}}:
{{formula:9c42482a-dbfd-4274-85eb-7c049ab65288}}
| m | 0313ebce7501438e22c458ca3801dc2e |
A basic task is the transportation of quantum states from one location to another. Ideally one wishes to have perfect state transfer (PST) whereby a quantum state at an initial position is found with probability 1 at the final destination. While there has been seminal work on optical Bloch oscillations in waveguide arr... | i | 3a2c992da059aefa99a4bf4c57a686d7 |
The most accurate current denoisers are trained on a representative dataset consisting of noisy images and their clean counterparts. The earliest method to do this with a neural network was {{cite:25b9290bc21eb020a3be3f8a5d4a8e46b2e04c7c}}. This was heavily refined in both the works of Mao et al. {{cite:e8fc6e4bf348a0f... | m | f87de6c1c3f0f90546de64c9b0085e53 |
A comparison between the abundances of ethanol and “warm" glycolaldehyde relative to that of {{formula:fa1a0cb4-601c-4a8b-8c29-1e53d674fb5c}} for each position is shown in Figure REF .
We found that {{formula:1c004167-1140-4428-891c-dba54c56b10e}} , with a correlation coefficient of 0.96. This result agrees well with ... | d | 53f3adf967d06924fd4fc9ce5e01475b |
In recent years, deep learning based approaches have burgeoned in the field of medical image registration {{cite:22488ff81589bc6f6f5921bb5a135031c8df4fe1}}. Their success has been largely driven by their exceptionally fast inference speeds. The most effective methods, such as VoxelMorph {{cite:f2b395a49d049c30df1ba4b50... | i | 84a35b5d62c74369fb25dac083af6334 |
There are many stories surrounding the origin of the Chicken McNugget theorem. However, the most popular by far remains that of the Chicken McNugget. Originally, McDonald's sold its nuggets in packs of 9 and 20. Thus, to find the largest number of nuggets that could not have been bought with these packs creates the Chi... | i | 65cb2a5bb48386c6a2a470894e5ae4f8 |
Considering how the presence of confinement affects the conformational dynamics of a chain{{cite:2ff6c4e378f75ea4decf9612eb79a017bf330796}}, {{cite:fc7b7b0a1db4d17db37cb3f25966b9e1efc31474}}, {{cite:04693fecbfdd6b3c3ed1bb090caa2d58571861a3}}, its outright indispensable to look at the influence of the geometric constrai... | r | 97b8ef444f3cacfc80fabca3e6f2484f |
Note that for SDE, {{formula:7a612ec3-4b11-41a6-acca-ed818aa177e0}} comes from two discrete approximations with different timesteps but the same Brownian path. To generate random samples {{formula:134eabd1-a276-4b65-b414-0a3c7091dc21}} , one method suggested in {{cite:b17d77b9e238eb083d44bed2956bfc49d2a951c3}} is as f... | m | de2df3adfab7bb52d830b75f918d1b57 |
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