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An important trend is to use large networks on external training datasets such as ImageNet {{cite:0303c6f7df627761512863314725482d9be2e4dd}} to model the distribution of normal features. For example, P-SVDD {{cite:61111a20831b686fb0ecaa4e6aaf71608b1658cc}}, PaDiM {{cite:5cece5899561e931007ea04483404065e8eabbd4}}, SPADE... | m | c5f27c0d30ebee3f66b97fee7a2cdade |
It has been known that the Palatini formulation {{cite:c5f6f61d00664eb260e7737c1f1efc70bb7f0611}}, {{cite:fc135bcce630858112a9820e4262902fffb388e4}} of General Relativity (GR) (first-order formalism) is an alternative to the well-known metric formulation (second-order formalism). In the latter, the spacetime connection... | i | f0b456385568a43e38d1fb4b4323e108 |
TorMentor is developed as a technology demonstrator that enables the encoding of domain-specific expert knowledge to generate plausible distortions.
While defining an augmentation is constrained by its formalism, the fact that an augmentation is defined once and automatically applied on images, pointclouds, etc., makes... | d | 70e3f9feb12deaf7ac7327b615079906 |
If a charged massive scalar field is scattered off by a charged black hole, under certain conditions, it is likely that the energy of the out-going wave becomes greater than the energy of the incoming wave. As a result of that, the outgoing modes at spatial infinity are amplified {{cite:d47525096094118f94f9b1f299afdb0a... | r | a45ff6aef65fcb44d7bd235100c2389b |
Whereas the criteria used in temperature - dependent specific heat and magnetic susceptibility, as well as in field - dependent magnetization measurements are outlined in many publications and are reasonably well established, it is less so the case for the magnetic field - dependent specific heat measurements. To provi... | r | 9c17870a590cfc1eafc3ddf3a13e1980 |
Allen and Dynes.
Building on the work of McMillan, Allen and Dynes (AD) in 1975 presented a re-analysis{{cite:f88e13b623b95ef654ef1d35bee920cc43d40d68}} of T{{formula:acdcdabb-54a3-4de7-897a-2a701d767007}} , using more than two hundred solutions to the Eliashberg equation for {{formula:63b041fb-9c8f-4368-a91f-c3c754660... | d | 0d30a993f6e703dcbf577418869b2f9e |
In light of recent results showing that the Sun has been able to give rise to several extreme SEP events which are likely not manifestations of unknown phenomena but rather the high-energy/low-probability tail of the “regular” SEP distribution {{cite:9eecf54d8839b8029f174dab43a180c14658b1d5}}, we have identified an upp... | d | 464c3814a59577a0367056da3c709cf3 |
Strengths and Weaknesses.
GraphVAE-MM inherits the strengths of GraphVAE {{cite:a93a2faa463fada94b0d1181ec80402908b6e70a}}: expressive power through graph embeddings, and fast generation due to all-at-once parallel edge generation.
GraphVAE–MM also inherits the known limitations of GraphVAEs: 1) We need to know a maxim... | d | 075723a0bccf575168796d50777783af |
with {{formula:46e5479a-a9bf-43f5-88c2-dd35f758ba52}} being the ground state of the elliptic equation {{formula:9b15eb26-ec6a-4f12-88a0-54b2feabd073}} , Holmer and Roudenko {{cite:99555f501777f5fbd2d815e0b7e1eeb00266d3b9}} utilized concentration compactness/rigity method to obtain the global well-posedness and scatter... | i | e4638bc7016405c8a34223cc781bbe3b |
According to the Perelman's seminal paper {{cite:0893980b156d00a1759b6cfdf1051fe1e18dd308}} the Ricci flow is an entropic based differential equation. In fact, employing an appropriate diffeomorphism {{formula:f7395138-c58e-4d5b-bf47-9d1d1320ae22}} , it can be seen that the Ricci flow is the gradient of Perelman's {{fo... | d | e86fe96398b6d34e19704260224b9547 |
We also compared the above algorithms with major CNN-based semantic segmentation models including PSPNet{{cite:245d7800c4b3aba9f65229f0636429f146d8579c}}, U-Net{{cite:7c530475822f1d56a3824effedb3ba999ea7efd0}}, DeepLabV3{{cite:73fd08276b4b7a79dc6d792258c79a93cd1759c1}}, FPN{{cite:9f0b649091ce7f20559d6c84dc7b7c2e4a4a634... | m | 1871be33bf6e3cb18d2b8bbb8f6419b2 |
In panel (d) of Fig. REF , we compare the cosmological mean metallicity ({{formula:6533cfa4-ed15-4073-9d0c-32d120eb58a4}} ) computed for
individual elements (e.g. Zn, S and Si) of DLAs and sub-DLAs (taken from
{{cite:b5cc62ed98e262270a71403608487a0741d4da64}}, {{cite:18c517b66d8c59ab5b3369c490ca35170fdf10fd}} and {{cit... | d | f9a58392549a08f7a4ac80fd1aec7909 |
For the plateau height of {{formula:f57a3dc4-6074-4dcd-ab24-0e52396430f5}} to satisfy the constraint on the inflationary energy scale{{cite:11ff87bfb83cd6d1b9b4348eeb57fac8953518df}}, the choice of model parameters must ensure that
{{formula:8df64311-b3ec-47d9-ba0d-ed8109a02d0e}}
| d | 9c5986083f8f994d79abcf86f3b1b4d8 |
As their name suggests, these particles are a generalization of the quantum chromodynamics (QCD) axion, predicted by the Peccei-Quinn mechanism in order to solve the strong CP problem {{cite:deea30477d3c5d09236ee3954e3a381c5c5819b4}}, {{cite:13e1fdddc5fc769d31d0fcb9de150e212bb54e47}}, {{cite:0640434c7509dfa53d8bb72a228... | i | c45037b4d7dea83ee21ea81c9dbe468a |
#5. Temporal action proposal model: to understand how well an class-agnostic action boundary proposal model can detect generic event boundaries, we train a BMN model {{cite:656b412193250fe50fb6a16d3a3e7361b00a82bc}} on THUMOS'14 {{cite:4fab543a6ce23dc2c38d5bd404449d18db6891d3}} and test it on Kinetics-GEBD to generate ... | m | 78d43dfb43c748075c96732dd6526d07 |
Results on Age Estimation. The comparison between SPUDRFs and other baseline methods on Morph II and FG-NET are shown in Fig. REF .
The baseline methods include: LSVR {{cite:75882c12dcb90dae8574d04c1641c495dde9e4d2}}, RCCA {{cite:64b70c51f1b39127878e887a5a7f3ba67dae2f95}}, OHRank {{cite:af0b99e7b2d072208a59d4a2627be2b2... | m | 01a3e22c8da25d3565003de8f4ee490c |
The ALIGNN-FF model has been integrated with atomic simulation environment (ASE) {{cite:76dbd337029981423a183078327b61cac4eed610}} as an energy, force and stress calculator for structure optimization and MD simulation. This calculator can be used for optimizing atomic structures, using genetic algorithm {{cite:ab1f62b7... | m | 2e13b25d8cc3ff216b3b7cc41c60ed20 |
Previous work in {{cite:d7bcc60c3070773b55efceb3202eb55e5648eace}} uses an autoencoder to learn novel, highly nonlinear modulation schemes that offer an implicit coding gain and are robust to channel variations. In another example, the authors of {{cite:eedde3745698ae4b083cc48dee01b472d3c7266a}} propose an OFDM-autoenc... | i | b318584dc1e4b908e5eb569788d9fbf3 |
Note that, after we factor {{formula:ae492683-f3c6-44c7-9dd5-2c211c56ff0e}} , the mixing {{formula:1affbd6f-c3bb-485f-964c-6af8a5793275}} in () of up-quarks with the heavy {{formula:1ad21eda-5e99-4cf4-98b5-0cfcf71d3807}} quark through {{formula:ec967261-d7de-4be0-a936-99af22320c87}} exchange is given by
i= v2YBi/MB... | r | 25df9246dc5d71b25bc5cd26d90d7ed2 |
Deep Neural Networks (NNs) {{cite:1d998eb7897b12dc279fa44a5362d8228a7bba6d}} have revolutionized many machine learning areas, including image recognition {{cite:374cdc6655dfbfad8e05fc3f9c56543b2738a901}}, speech recognition {{cite:c702648d2e51277275a2a2811324385c585cb0da}} and natural language processing {{cite:74f5802... | i | 075e2096df689d80c1fcd9690df560fb |
In this paper we are interested in on-line estimation using recursive algorithms. It is well known that, in contrast with off-line estimation schemes, on-line estimation provides, via the accumulation of past measurements and noise averaging, stronger robustness properties. Moreover, if the adaptation gain of the estim... | i | 44c1a117bce3279103cda2405cfc1069 |
Continuing their great success in many areas, DNNs are being deployed in critical systems such as personal identity recognition systems and autonomous vehicles. This creates great security concerns about the DNN deployment. In the recent years, researchers have already investigated various types of adversarial example ... | d | 15083220e18b0a1416d540dd5fdc1dce |
Wormholes in General Relativity (GR) are solutions of Einstein equations presenting hypothetical tunnels connecting different parts of the Universe or two different Universes. The first discussion of a wormhole configuration was presented by Flamm {{cite:6ea8843403d05a8f55c41d485456965230574c3f}} and later Einstein and... | i | eca1ce59c9ddadbb7bbdc8810d7c16db |
We apply both the distillation algorithm and naive substitution in DQN (in which we simply substitute the deep neural network in DQN with a neuro-fuzzy controller) to three different OpenAI Gym {{cite:b488a10bb170d2cd94311c0ab7eb624ecbabc698}} environments: CartPole, MountainCar and LunarLander. In the CartPole environ... | r | 6a921e6a925c5acd70d29c6f4cad7ee2 |
Due to the boundedness of the sequences {{formula:a1723a11-3a1c-4c2a-9f63-febfb3c208d4}} ,
the convergence {{formula:84758e32-bddf-473d-9f6f-29c58d2eeeff}} as {{formula:dc02587a-754c-467b-904e-86548af862ed}} for all
{{formula:924d0861-c97f-4c95-a7e6-c107529c2c19}} , and the outer/upper semicontinuity of the
mapping {... | m | acfe32c24ff796b9733b8baa9b2ebcfd |
We have calculated LHC bounds upon four models that have been fitted to {{formula:eef87f5a-cc46-4323-a027-5307d02222f6}}
anomalies. Each of the models includes an electrically neutral, massive
{{formula:8b8ab2a7-189f-476d-ae7f-a8d27001fab9}} gauge boson which has family dependent couplings to SM fermions,
the most im... | d | c74b6dac64d6850ed8a4a95a66cd6a3f |
The property of {{formula:14fbd242-0e07-4e20-be07-b2faaf94320e}} becomes a very interesting topic since its discovery, because it is generally thought that there are not enough unassigned
vector states in charmonium spectrum (taking into account the recently reported {{formula:9a5eb95c-2f6d-4a45-831f-d3051eda6acd}} , ... | i | a34ab1d0a0749c82fa44651231e0bb1b |
On the other hand, three hidden-charm {{formula:d5519123-c317-43e7-af20-e2d87a1b5a2a}} pentaquark
states were observed by LHCb collaboration in recent
years {{cite:32f797367291138211a522fe64989a6eec101a87}}, {{cite:1b4dc1302b696b3268cf3d44f720b05dbf7e79fd}}, where the experimental data
are in agreement with the predic... | i | 9f9618762c209344c6f84731f5004ef6 |
where {{formula:68856c88-5f01-493f-bb64-14b5a42ff400}} is a regularization parameter, and {{formula:ac380e76-6f36-4008-9fa5-19fdb75f3f97}} is the projection matrix (see {{cite:12f87282adbfcd5e3163ac7d8a5767ccfdbe0e50}}) which will be learned jointly with {{formula:cb13f471-0caf-46f8-9374-8fb8423d90f9}} . The whole o... | m | ef42bcd385140ff25f3a92860ad93e6a |
Qiu et al. 2018 {{cite:7593b8bb941a2d028a7cf814478508bcaf4e30b4}} SAE Epilepsy Normal, Interictal, and Ictal From Andrzejak et al. {{cite:679219f58a4afe9b829b1e90079bfe77e3a88236}}, 10 Participants (5 Healthy and 5 Epileptic Patients)
| d | 1d0528da39df45ea85fe0d780abe04ff |
OCRA builds on capsule methods {{cite:378b10b52292bceb3af96240ae4c4f7f898bb0f8}}, recurrent attention and DRAW architecture {{cite:afa15ecf61568b00e09c5d32f0b214ba6ddb3e13}}. While it addressed some of their limitations, there is still room for improvement. For one, we believe that a better capsule routing algorithm wi... | d | c1f4871348eaea621e6555ba5ab7b523 |
In our simulations of LIF neurons, we compare against the Akrout method {{cite:bd396e66fa2bc1c5673c10acd4dc3e2f094567b3}}.
This rate-based method makes use of an inference phase in which neurons are stimulated (with mean zero) and then the levels of activity of input and output neurons are correlated to form a weight e... | m | 2208f1e52caee10c4f981db8462485cd |
Our study found that CNNs for brain MR segmentation can exhibit significant sex and race bias when trained with imbalanced training sets. This is likely due to the algorithm introducing bias and/or the well-known effect of representation bias {{cite:09ee951e80aa71c5065ddf1cd28300b778b55108}}, in which distributional sh... | d | 404e04e0d94d911f494559578a04211c |
Tables REF -REF present compare our results for logical structure prediction from the table image on tablebank and pubtabnet dataset, respectively. The scores are obtained by averaging the score for every table across all the tables in the evaluation dataset. From the tables, it can be inferred that despite trained wi... | r | 81495d015fa390d38504b943916b683a |
In the plots of fig1 we verify the pretty stable mechanism
{{cite:0e6cb80decc9458070d7739b9c387dcbd4a9d025}}, {{cite:8773dad0c84cb3c59405b16f1c9465a82947fda6}}, {{cite:e486758940ae3380929aa8456a058ed9879bd05d}} which establishes T and E model
inflation: {{formula:9988edf5-08b5-42e8-a550-ffdcbfa29a5b}} expressed in ter... | r | 8bb880a799f9d96e5d965873d078512f |
Studying the high-redshift (high-{{formula:923cdecf-54a8-44ce-bb85-f34573b20167}} ) universe allows us to investigate the first formative stages of the Universe. Among these stages, the last one to occur is cosmic reionisation. During this stage, the ultraviolet (UV) and X-ray photons escaping from the first galaxies c... | i | 8e2901fca4704dde56f1d3453e2f4d4a |
Theorem E.2 (Martingale Central Limit Theorem {{cite:e6653f29edc1af82618078a78c780ad65467af05}})
Let {{formula:2cd6726d-4cc2-4e35-9658-53f5e08e9367}} be a square-integrable martingale in {{formula:22e18919-9686-4c71-85b6-e4b38e5a1542}} adapted to a filtration {{formula:cfbe225a-64e9-41db-aab1-a6b5ba767042}} and let... | r | b6c8dd722c57afecbac891afe9420941 |
If the two temperatures we have detected are a simplified representation of a range of temperatures, then the properties of the two components should be correlated. Figure 10 compares the EM of the warm component to the EM of the hot component. The best fitted linear relation between the components has a slope of {{for... | d | 8024919469a667b8edba082b5eb5ecb4 |
For all three data sets the full AHC solutions, employing single linkages, were also computed for comparison. The water coordinates
were used as is while the two larger data sets were processed by transforming to standardised values, by removing the mean and dividing with
the standard deviation across samples or pixels... | m | e61845a069a174b9e167280e428b033e |
For KL Routing, experiments were done on a simple unsupervised perceptual grouping task {{cite:22cf549a9904b010f509cedf3cb62172775bf3ba}}, where KL Routing performs better than dynamic routing. There is no comparison between EM Routing and KL Routing, but given the type of task, it appears that EM routing will also per... | d | ca194d8c88b8c69dad9353ad0a27198e |
In the meantime, SGD with momentum acceleration (SGDm)
remains the current workhorse for the state-of-the-art (SOTA)
centralized deep learning training {{cite:d007d8049baf90a382bb492b5330bf1cc3cff15b}}, {{cite:822660ea280f1d9b2eb0dff1dd96269a4a2a7faf}}, {{cite:6fadb4bf3fd5e03f312928f5b78b21a7a9510b4d}}.
For decentraliz... | i | 04787f2003260cbcca29ccf2e0d29149 |
classification model which is based on word embedding, thus we applied fastText
https://fasttext.cc/docs/en/
word embedding tool that represents words as vectors embedding.Those vectors embedding was trained on Common Crawl and Wikipedia. We used the Arabic ar.300.bin file in which each word in WE is represented by the... | m | d7c9b5483b615d2d09b39c04f2b7e5f8 |
We now present our simulation results for evaluating the performance of the proposed algorithms. The dense C-RAN is assumed to cover a square shaped area of 700 m {{formula:4452db2f-0107-4950-9eb2-708f593417c6}} 700 m. The numbers of RRHs and users are set to {{formula:d246ad52-7e1e-406e-98a7-4a8405145407}} and {{for... | r | a76e3ed0744920f68eada1841407bc17 |
Reviewing the gravity models, we find that three groups of authors independently employ different ideas that lead to equivalent results (within given parameter configurations).
We interpret this observation as strong support for the gravity idea, i.e. that some sort of interaction decays as a power-law with some sort o... | d | 8504340e8e308678949ce29e8c3f68b8 |
Perhaps due to the needs of identifying causal relationships, the study of DTRs originated in causal inference, with the pioneer works of {{cite:122a242447f2b76bb6783f2a68a5c3f39bd12145}}, {{cite:e751441d8e1d509c482c3f295557fa835832f230}}, {{cite:576681d4c07579e4c6727885eb4d5458eb8f233b}}. Over an extended period of ti... | m | a5c92a68d4c773a8ffc292666b816afb |
The predicted masses of the {{formula:938ebd6e-c0d0-44d6-b0a6-783257f1d8ba}} baryons up to {{formula:2bffd7a3-2b30-489f-9f13-75d2b164a709}} shell have been given in Table REF and also shown in Fig REF .
For a comparison, some predictions from the other models are listed in Table REF as well. It is found that the ma... | r | f25b9af5db1c9a347c926692c54145d9 |
To verify that our method is easy to implement, as we mentioned in the manuscript, we explain how we can apply our method to Soft Actor Critic (SAC) {{cite:7e8722043820efc46faa3d6a893f999edac507fa}}, {{cite:0ba1b07789f94091405927b74bb8fc7cea1f7293}} based on PyTorch 1.7.1. In SAC, it uses double critic networks and the... | m | 253c706e3d74045d2337b463c6420908 |
Having introduced the notion of an abstract trace map and Green identity (REF ), we switch to symplectic description of self-adjoint extensions of {{formula:2f5f006b-6dec-4734-a2e9-6de4689444f2}} and a symplectic version of the Krein resolvent formula. We note that the right-hand side of (REF ) can be written as {{for... | r | d87c031eb149f34cd8aca763d8343d72 |
The current version of the algorithm assumed bright objects on a dark background. Depending on the raw image material, additional preprocessing steps such as intensity inversion, contrast adjustment or even more complex methods such as vessel enhancement filters might be necessary to produce reasonable results {{cite:e... | d | 99a29a0203cc5197205a212107b65230 |
Contribution.
We demonstrate that our U-Net architecture is able to accurately predict surface wave dynamics in complex straight-sided and curved geometries, even when trained only on data sets with simple straight-sided boundaries.
Our U-Net is able to simulate wave dynamics four orders of magnitude faster than a stat... | i | fde5829bd1e1115afd93e843df385f71 |
Proposition 3 [{{cite:8c45c1f4916ffa07959c219cf4811383d3b12f58}}, {{cite:b54ab2799eafea2c9a4d8f074b847896764914c4}}]
Let {{formula:17b4308c-01e0-47b9-a1c7-c0b6812c6cd1}} , {{formula:74441c0a-74d4-4ff3-8060-9f87f1fea5a1}} and {{formula:12115da2-d57b-4190-b1b4-45c50870d28e}} . Then,
{{formula:1abbf728-db75-4579-9e85-77... | r | cb6a8178a842dce16459512b2492938e |
An alternative to deal with the non-differentiable issue is to use a continuous function to replace the samplings. After a multinomial distribution over the words from a given vocabulary is estimated by the generator, a differentiable sample, Gumbel Softmax for example {{cite:b623e6161f2b09e34e9f5b92b865ee1b90a5795d}},... | i | d48e7cbc1ed2aa10bdc33f677dc23e8a |
The most common class of explainability methods for image classifiers visualize the reason behind the classification of the network as a heatmap. These methods can make the rationale of the decision accessible to humans, leading to higher confidence in the ability of the classifier to focus on the relevant parts of the... | i | 74d2ad8f84246b2f7e819d26c9333c12 |
Then, assuming that {{formula:673c8d49-88a6-4a79-9d78-912726f27bdd}} is big enough and requiring other technical but mild conditions
{{cite:1721285575faaccc1dac2d0ffdebc433a95fb4ac}}, the constrained problem (REF ) shares the
same solution of the penalized unrestricted optimization of the Lagrangian function,
that is ... | m | 285a454150588e93f33eb109c27db3b8 |
A vital part in the Langevin MC approach is choosing the step-size {{formula:94d4ae30-386d-42ca-8581-0341f3a04655}} . Here, in this work, the choice of {{formula:23f91705-f6df-44aa-8496-870578060add}} is picked such that the acceptance rate in MALA is around {{formula:bbd6b82e-a7e4-4cec-8bc6-cfb3663bfb2d}} , motivatin... | d | a261ef1cf6f5857c6b45b76fcccaf3f8 |
We report snow simulation results in Fig. REF . As the figure shows, 3D Stylization changes the floor texture but cannot add physical entities to the scene, limiting its realism. Swapping Autoencoder {{cite:a3ab123e3614bd44d4dbe1f0765c76fa06f74617}} changes the overall appearance but hallucinates unrealistic textures (... | r | 9b005da8a869523229dd70e1f4fe12c6 |
During the decay phase of two bursts in Obs 1, the oscillations are found with {{formula:2f6c90e5-e233-4e11-8278-a4d7000f6348}} confidence. Decay phase oscillations are generally described through the cooling wakes {{cite:22494acd6b003ff186b0b5393d0350b6f19f14d6}} or the surface oscillation modes {{cite:71c5595cf0fe57... | d | 9d3c03983ba37bc2c644364aeff36acb |
Table REF summaries some of the other annihilation decay of the {{formula:1032c2a2-b59a-4999-8e5b-a6c59fd51b82}} into {{formula:ddb26a2e-7649-4369-a2d0-56df41ca1f69}} and {{formula:fb2c87c4-bf6c-40be-96e0-fe6aa1f56bfb}} . As far as the {{formula:78397af8-0b2d-40e7-be93-5a47356f2e3d}} concerns, we find that present ... | r | 11c39d226544a33a121e4f125604fd80 |
Deep neural networks are often considered black boxes with only limited possibilities to look into and comprehend their decision-making processes.
However, due to their state-of-the-art performance in an increasing number of tasks and the advantage of applying them to problems without domain knowledge, the necessity fo... | i | 3ce5a5a120b0c87a238364b4f6b3eaf0 |
Holographic models from string theory {{cite:223048228d330bbeed37110e37dba161ee87cec0}}, {{cite:1da6c058a29705ec7393a0665f5170f9c8708191}}, {{cite:fc0cafadad7377dee2213c2f1fdb1761153779f8}}, {{cite:29aaa8dc7c9bb4869165e9f4ad111bb13261b8a1}} have been extremely successful in describing a great variety of quantum gravita... | i | 8c79562be2ae57682dc798bb37ee0a00 |
The core novelty is that the model is trained to improve the quality of its explanations by using diagnostic properties of explanations as additional training signals (see Figure REF ). We select the properties Faithfulness, Data Consistency, and Confidence Indication, as they can be effectively formulated as training ... | m | 37f0553f3ca41902119012d24e21c5eb |
In this paper, we consider a natural extension of the gravitational Schwinger-Keldysh path integral prescription of {{cite:b507d3b8f82e5c15708278025c745b47a2f1bd9d}} to rotating BTZ black holes. The gravitational space-time asymptotes to the real-time Schwinger-Keldysh contour of the dual rotating CFT at a given initia... | d | 9414748ecc568beac6b5b27986131dec |
After dealing with the theoretical treatment of electron-nucleon scattering in the absence and presence of a laser field, we will explore in this part the numerical analysis of the obtained results.
As mentioned in the theoretical framework, the DCS of the electron-nucleon diffusion has two factors: The number of neutr... | r | 93fdc827fccdb4d1e15dc69204758c62 |
First we discuss string-averaging methods in which a single pair {{formula:61e43f00-c1aa-4e70-89cf-f666cca2b50f}}
is picked at the outset and kept fixed throughout the iterative process.
Such string-averaging methods will be termed “static string-averaging
methods”. We will make use of the convergence theorem in {{cit... | m | 9f168e7713b8085611e5c64572845243 |
In this section, we briefly review the basic features of each method employed in our work. A more comprehensive analysis of the GP-based techniques used here can be found, for instance, in {{cite:1ae4b20f45c37417de69b3461396710c138b258b}}, from which the discussion below is largely inspired. In order to compare our GP-... | m | 9d2cc3be04662a42fdf39360b5193d2d |
Remark 3.9
By invoking an argument
based on the central limit theorem
(see {{cite:8cc2accd9b6bd520678dda3306382d245d103123}})
the Kahane–Khintchine inequality
for Rademacher sums (REF ) implies
a corresponding result for Gaussian averages:
For all {{formula:87219812-60a1-4b02-8a43-29ea418c46dd}} ,
for any orthogaussia... | r | 33b141e536880cd3dd7dd2e0091ec903 |
Theorem 6 [Theorem 1 in {{cite:491817baab9b2bb01a82f47e0512e4dad43e29e8}}]
For all {{formula:3343b843-5224-41a9-9b85-7bfc4613602b}} :
{{formula:70a6c725-0df9-4271-83f2-3426dff4eb78}}
| r | 24ffffbbc7e84a009ebba1267de0596d |
The question remains why Mrk 335 is no optical Seyfert-type changeras observed in an increasing number of other AGN {{cite:d847c243ea892b483a23817afeaba5a9a8f89290}}
despite its high amplitude of X-ray variability (a factor {{formula:1cc5905a-37c7-4cbe-b40f-9915c44814c1}} 50 between highest and lowest state in our
long... | d | e9d5e90c1d8852a7594397b158b298c9 |
It is possible to accelerate the rate of convergence from {{formula:9a46f6fe-05fa-4d3b-b8ae-31c4de028f77}} to {{formula:1866333a-de6e-449d-806b-1fe0b4f435fd}} for gradient type methods. The first acceleration result was shown by {{cite:572a9f1a29e2076118c526f88cc9f87897b4f076}} for solving smooth unconstrained proble... | m | ce8234f9ae8e81703caf921b8e2992f2 |
The results show all RGB-D methods outperform the RGB based methods. Even with only 20 sparse depth sample, the overall accuracy is greatly improved. Our approach consistently outperforms the state-of-the-art {{cite:33223d582b3baf8347445bc06ead855273dd7ee4}} and others {{cite:49348c5ed2a113a9ed6f5c39d732d3d76e6a66a7}},... | r | 111823929933dec9db9ecc3f43dc58f6 |
We consider following schemes for comparison: 1) PDCA: the proposed PDCA joint-design scheme; 2) AO: the alternating optimization (AO) scheme proposed in{{cite:0a1e35acea5e94ad229f0e47bf7c4013177f1566}}. To be more specific, on the one hand, the RIS phase shifts design problem is solved by semidefinite relaxation (SDR)... | r | 00360e213e56f46b2ddd80be285bb469 |
As we have discussed above, we adopt a single pyramid framework. We hope the features of every single spatial size can independently learn rich multi-scale information. We notice that layers within the same spatial size also have different receptive-field sizes. Thus, aggregation among these layers may also be able to ... | m | 3fcbf475f9928bdc7dd2f1d132128ad2 |
It has been shown {{cite:96f030483b4943b719c6d87425d0c573b84a6fef}}, {{cite:55ca68be9c76bbdbe29b7204b7dfaaba1b933182}} that the update (REF ) enjoys {{formula:cdbe4cca-691c-4b49-ac0a-a842d0ce4119}} rate of convergence. In this section, we show that this algorithm indeed has asymptotically geometric convergence.
| r | a05678bdee10e160f72265fcd770e585 |
Next-generation wireless communication systems are expected to provide a 1000-fold increase in the network capacity over the operational system for satisfying the ever-increasing demand for higher data rates driven by emerging applications such as augmented reality (AR) and virtual reality (VR). To achieve this goal, p... | i | faf267096871657e6797581298cd2cb8 |
Novel View Synthesis (NVS) aims to generate images at new views, given multiple camera-calibrated images. It is an effective line for realizing Visual or Augmented Reality.
With Neural Radiance Fields (NeRF) {{cite:7c0a4dea25854b0319dc85becd48504774b3afe7}} proposed, NVS tasks {{cite:b768306c0afb4ef1ef39c44a72d56e2b70e... | i | 47a1e97f5fb15d2d41bca4720c621087 |
We first reviewed the expansion due to Girvin and collaborators (cf. refs {{cite:6123228cd0e3cffcc33031e09e97a62b6e939f22}}, {{cite:60145e9e527764c215f90628c567f0fc42f10fa0}}).
This expansion is ill-suited for extrapolation to the thermodynamic limit since it is highly non-orthogonal. As a consequence,
it renders cause... | d | e27b10938c6defe8e9bd6d607dfbe7ce |
Quantales were introduced by Mulvey (see {{cite:79dfd31ed40995f89d6d16939a9d75b917ccb5bb}}) in order to provide a lattice-theoretic setting for studying non-commutative {{formula:ded1ba6e-cac7-4c75-9a59-adf381aa5592}} -algebras, as well as constructive foundations for quantum mechanics (see {{cite:7186ba5ef394e0bdef... | i | ab077315735bbc83f89d8f43855493f0 |
This is a common quantity of interest in causal inference and we choose to estimate it with the common difference-in-means matching estimator, defined for some match assignment {{formula:3fdb9964-8e25-4634-b7c5-63ddfba2fac8}} as: {{cite:a204ab07035e8fe4a3c50659e456a6c06891b192}}:
{{formula:e79e3799-97a4-4ed6-9f1e-109... | m | 329add4a4c7d4155f0a13aada17c5807 |
The Hubble parameter at the second lowest redshift must be computed using the third, fourth, and fifth galaxy (counting from lowest redshift), as they yield the effective redshift {{formula:f9d0d078-522f-4e37-bae3-38ade53871f7}} and {{formula:56171da1-acff-4e87-a387-fdab9c3693ad}} km/s/Mpc. For this value the uncerta... | r | 2c282bb1dd93bd9f55e08cae922c7c95 |
The electronic structure in the vicinity of the Fermi level in the dimerized phase is shown in Fig. REF (c). We used the local coordinate system with coordinate axes pointing to the oxygen ions. One may notice a strong bonding-antibonding splitting for part of the Ru {{formula:e92d1ad9-1f7c-4d08-89a7-6f9a10005d9d}} st... | r | 3c13e5dc200d34886a8990492a14f43b |
An alternative approach which yields larger ROA is presented in {{cite:2e8f436e59273de1c111478a90885e2df8dd6ae4}}, which uses a disturbance affine feedback gain to parameterize the control input, as {{formula:74ba1824-19f0-4d1a-82be-85189a6920ed}} , for {{formula:1c2e0bda-0194-4d18-9c5f-de51047e406c}} . In this method,... | m | 58ae59237b346058d3afd0d7aeaf5abd |
The sky signal is a composite of ground-emission spillover, atmospheric emission, and cosmic signal attenuated by the atmospheric absorption
and is beyond the scope of this discussion (see {{cite:6b940942faab4a450636c62ced8b52c696820d46}} for more information).
If two measurements of the sky are performed along one of ... | m | a626323e5f519dfc23622bdf00c770b4 |
SLAM Integration.
One benefit of our method is CPU-friendly and can be implemented in real time. We integrate our NDD into existing LiDAR odometry and mapping{{cite:c42ad2c619b7d77c0dea6a711bc23c30822e765e}} (LOAM) system for loop closure detection, as shown in Fig. 6. NDD-LOAM is accurate for loop closure detection an... | r | ff36150242dc47361c234f4afe252905 |
Also to compare the predictive accuracy results of our method with others here we used Diebold-Mariano test {{cite:3ff8638b3fe58b5bda964d04a735f183d7460bf7}}. Base on the test, the null hypothesis of equality of any two given methods at the {{formula:546a631f-492a-4816-b372-53bca54dd2fb}} confidence level is rejected ... | r | 005886cbb0bcaab419a7a47d85488844 |
When {{formula:3591365f-4adf-46cb-97a9-fcfc35113237}} , the designer decides how much data to sample without controlling the type of data. We explore classification on CIFAR-10 {{cite:8e9c650369425a233ae811082ad39a6b841b89ac}}, CIFAR-100 {{cite:8e9c650369425a233ae811082ad39a6b841b89ac}}, and ImageNet {{cite:5fcb7d09553... | m | 1eaea1f7abef6612dd3dd5fe2051d9eb |
The first motivating point for this paper and its prequel {{cite:8155f31b8acae2096ff622a987b71361c8c5f6f2}}, suggested to us by S. Shatashvili, concerned precisely the last item: namely, the systematical understanding of the relation between 7D abelian Chern–Simons theory and 6D Kodaira–Spencer {{cite:5022f55f27b2a4532... | i | bf25099aaaae0f426250c4c857609925 |
DFT calculations. We used the generalized gradient approximation
with the Perdew-Burke-Ernzerhof (PBE) density functional {{cite:88d8a5e5c491907756c742b2b8da1e64a39c7e0f}}, {{cite:6380983478575c95369e7f7687fdf1a03e8fbe6b}}
implemented in VASP {{cite:4408a62bf68c0f23b9fbd2f3aad3cbade7e574e8}}, {{cite:9c62e80dbcade384a9b... | m | 2053c2244961c668dc1008064e2b4ea9 |
Importantly, in order to account for all the above empirical
phenomenology, the model needs to assume multiplicative
variations, i.e. that the variability between the parent's trait
and those of its offspring increases (linearly) with the parent's lag
time: the larger the parent's lag time the larger the possible
varia... | d | 38f0721a4dd24d401e1627ee187327eb |
We bring the study of adversarial robustness to the field of neural combinatorial optimization. In contrast to general learning tasks, we show that there exists a model with both high accuracy and robustness. A key finding of our work is that the assessed neural combinatorial solvers are all sensitive w.r.t. small pert... | d | 85132837f2dbacff2972a6a44f9c1cf3 |
Discriminator Network.
We use the R50+ViT-B/16 hybrid model pre-trained on ImageNet from ViT {{cite:c1b05ca8aeb70fe220298fef6c64864f2760d6a4}} as a starting point for our discriminator design, in this case using the pre-trained strategies to learn effectively on the limited size target task data. Then, we simply appl... | m | 80ae41c66010c00a4880e1b2ebb316d5 |
In finite precision arithmetic, due to the influence of rounding errors, the Lanczos vectors computed by the Lanczos bidiagonalization gradually lose their mutual orthogonality as the iteration progresses {{cite:a3d1e023ed60e34b77001cd3e4f8743fca22156e}}, {{cite:8daa3d1c8b4ab24c617ebc39229f1cfea778611d}}. This is a typ... | i | 68d76b74d9647c2e54e73ece49df674a |
Table REF shows the end-to-end results on Spider dataset.
Based on the codebasehttps://github.com/microsoft/rat-sql provided by {{cite:c3287c6b9fd90b1ceeed1bcb445c6fb4ed783011}}, we replicate the RAT-SQL + BERT large model, achieving 0.665 exact set match accuracy on the development set.
This matches the RAT-SQL V2 + ... | r | b8a8fd5994065270c3450be5aff5fde1 |
where {{formula:9dd45d58-e16c-4971-b0f4-5fa0b3d715d0}} and {{formula:ba9fac0f-5c02-45a7-9221-f8642af75e44}} (see {{cite:d47d704da2619ba4916ec3f3c952dbf0e2af10e8}}). In particular, for {{formula:64a9f44d-ddba-4991-983c-1a5bd43e03b4}} , we have {{formula:7b3879fd-460c-4e30-9d09-1569de76c487}} .
The following estimate h... | r | 0b70425249752a1935ffd695e830df75 |
Galaxy surveys have revealed a strong bimodality of the galaxy population in
colour, star formation rates, and morphology {{cite:d16c9df6ce466b66ce7643be822b1cea270770a9}}. Galaxies can indeed be broadly described as either
red, predominantly early-type galaxies, with low or no star formation
or blue, predominantly lat... | i | e81235c37bbaeb1c0ad671d61840c02c |
Definition 3 {{cite:d47d704da2619ba4916ec3f3c952dbf0e2af10e8}}
An analytic semigroup is a family of bounded linear operators {{formula:9400f07a-1772-4b29-9918-0a6d78af5125}} in a Banach space {{formula:3716d64b-28f4-40df-94ab-4cb7ae1732dc}} satisfying the following conditions:
| r | 44812c257f5ee6531f2f34072e0b32a3 |
It is an open issue with regard to the question of whether jets are launched in the soft state, that is, in the thin disk mode (see also {{cite:9f3f42868122737770c7885b085b47a867a27021}}). The leading model for the jet formation mechanism is the Blandford-Znajek and Blandford-Payne mechanisms ({{cite:65c9b77f941cdf20a8... | d | f98f848ef64947ce206617b2544b85e4 |
We start from the effective structure factor {{formula:c04b860e-799b-4547-86ac-ad564044b001}} , which
represents one of the relevant quantities for the variational
approach proposed in this paper. In the upper panel of Fig.
REF , we plot {{formula:e9440d2b-cc1a-4d67-b554-62df63552335}} as a function of the wave-vector... | r | 770b580a7037eb13a72f63aa2845969f |
As it is custom in the classical deterministic Krylov–Bogolyubov (K-B) averaging (e.g. see {{cite:9d61373e3da70bc71b6612fa2058d7c98cbfea4f}},
{{cite:8a04d38f6ec85df6b13b641915f4035bdd761e95}} and {{cite:c0e1eef367ea46070fb13eeedadd6d06154fe1ac}}),
to study solutions {{formula:995016aa-ac75-4b64-9d41-bf30e258b6c9}} we ... | r | eb7254d4f0ee2747db14b8cc21f4973d |
We are interested in understanding when (under what conditions on the distribution shift) and why (via model properties) neural networks can exhibit effective robustness. We perform a systematic study of three tunable "knobs" that are available to the neural network practitioner and have been shown to impact OOD robust... | r | e1a46c3b60fbc7671335f025f34f5a06 |
In this paper, we explored the behavior of entanglement of purification (EoP) for different excited states dual to asymptotically AdS geometries. We used the holographic proposal established in {{cite:62435874ab3073862ae0670280c3c9b66cae128b}} for computing this quantity which gives the EoP in terms of the minimal cros... | d | 11ea64ee1743d2afcc77b30bbc52cd36 |
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