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This paper details the investigation of the KHI and null point collapse around an axisymmetric, linear null point, an idealised model of a real null point (such as that observed in {{cite:1aada1bb8bfccef875dce76971aa36ec0c8c4b5d}}). The impact of different null point configurations such as those with asymmetry (e.g. th... | d | 66dac8a244b02d6fb688b68164a2afbb |
Firstly, with the measurements of the central velocity dispersion and
the location of multiple images (Einstein radius) of a strong-lensing system, the ratio of two angular diameter distances
{{formula:44ad3e3c-002b-495a-b467-f1a266ed845f}} can be precisely assessed. Specifically, by
assuming a power-law model to desc... | m | 2a91fe135e5947f1069cdf250a76cef2 |
Figure REF shows
95 percent confidence intervals for {{formula:527f4506-fd04-4861-8c42-e2ec8ca4b7c4}} for each state
from the marginal structural model in (REF ).
We computed standard errors as if the weights were known, which results in valid
but potentially conservative inference as long as the weight models are
co... | r | 3352ec9a0357a14108a8d1217a088423 |
Theorem REF and the estimate (REF ) guarantee that the minimizer of {{formula:5b2b7f9d-36cb-4795-8b2f-bf64dcc2d89e}} can be found by the popular gradient descent method.
The success is due to the hypothesis that the desired minimizer is in the interior of {{formula:7c393adb-1bc3-4ccd-b393-0936fb7db33b}} .
We do not e... | m | 5f45c2ac551eac4d25589b7c1959420c |
This definition is equivalent to the concept of uniform stability defined over the on-average loss {{formula:5c9844ed-72c0-424e-9c3d-d8adf9cdabc9}} . Suppose that the loss function is uniformly bounded in the interval {{formula:919ade42-f487-44ef-9156-112eceeb6b84}} . Then essentially it has been shown in {{cite:2df458... | r | da64107af0dd8dcb908d3b47b215e865 |
Development of such a model class as something which will scale naturally to large networks is of further interest. Computing gradients on arbitrary Riemannian manifolds may prove to be challenging when the positions are in fact latent. One promising approach we plan to investigate in future work is that of product spa... | d | ad2ca68a48d26daf8431579317c951fa |
Note that we can chose the smoothness {{formula:6f67b170-3270-4158-a314-cfb38b13a33b}} of the basis to be as large as required and hence will omit it in what follows. For more details about wavelets see {{cite:5e1485e53b3f383d1867784873b4e6ad76b95826}}, {{cite:21c873ac00e73dc9c8dce0ff044db33f6cfcb162}} or {{cite:d9e7... | r | eae1d0a9be153d1d3d175e9240eb7ff3 |
The methodology proceeds by the translation of semiformal specification to Focus {{cite:5b2c31e2d25f91a1b4587ff566d2e4b7f6ecd703}}, a framework for formal specifications
and development of distributed interactive systems, preferred here over other specification frameworks, since it
has an integrated notion of time and... | m | 102f7ecb2e263d6155e7ec1193a901cf |
A fundamental problem in representation theory is the description of all irreducible representations. We are interested in the polynomial representation the invariant differential operators with respect to the generalized symmetric group.
We know that the direct image of a simple module for a proper map in semi-simple ... | i | 0b58a85a43423ccb4204a0a45458e27c |
Perhaps the most important ingredient in this derivation is an analogue of the property referred to as “one-sided molecular chaos” in chapter I, section 11 of {{cite:fbc0cfc61034514cb035b815770842495c894bef}} — see also Sone's lucid presentation in Appendix A, section A1 of
{{cite:36d49be54e4ce09f6441b6c23a70cca8321dc1... | i | e8fe322c3d6403510ce1b6456d56bb68 |
The density method does not involve the Ahlfors-Beurling operator nor {{formula:78e93a37-75d4-4864-9499-813464103c5c}} spaces beyond {{formula:bc9df394-8044-4702-aec8-69a77965aa9f}} , {{formula:57435331-25c6-4a27-89c3-e5c072d33389}} .
It involves the notion of distribution and the Sobolev space {{formula:bbfd367a-60d7... | i | 3691e801ba86130846ebd939a7f5184e |
Non-parametric methods find the sparse network by repeating a two-stage procedure that alternates between weight optimization and pruning {{cite:98fb82ca8a1088a6a3b754f72c25b7e8a564cf68}}, {{cite:68742ce04d5a73d92aa19cd982584999ed0b3df0}}, or by adding a proper sparsity-inducing regularizer on the weights to the objec... | i | c07a39ae3380365f0826fc971dbdea46 |
Recent years have seen a lot of studies which focused on the application of network representation learning methods for recommender systems and the user response prediction. Motivated by the success of CNN and RNN, there has been an interest in developing neural network based models for the graph structured data. Consi... | m | 5481f44575662c7b52519394ab0c956c |
There exist two main trends in the literature when it comes to measuring improvements in the learning capabilities of agents. One approach consists in measuring performance after a limited budget of interactions with the environment. While this type of evaluation has led to important progress {{cite:9a35092940d5f33b14b... | i | ee6aa981dfe900dde8993f694dac15ab |
The main contribution of this paper is a lightweight transformer neural network that exploits only depth information of range images to achieve place recognition. Our approach is very fast to execute and at the same time yields very good recognition results. Based on the attention mechanism of the Transformer {{cite:45... | i | cf8bbfac116722c8dc4a7d62600b346b |
It is becoming increasingly common for companies to make use of machine learning (ML) predictions in their services {{cite:3944fac99c875f06a867af774d0d952186fa6ed1}}, {{cite:f866393c5540e6593439421a63c4bd255bd851db}}, {{cite:fb72e3763b25d7db7f900446f7fa815cba4b24c4}}, {{cite:b5fc7fe4039e20db7f2c1f82c0dd99beae345e7a}}. ... | i | 9605b687e9446d44b11e5be020fec1c8 |
Predicting an answer in a KBQA system depends on the ability of reading-comprehension that is responsible for fully absorbing and understanding the question {{cite:3a3bf63a97974812f934f4100338d1d11da02f74}}, {{cite:a97434ee8b3d9e95f0e171ace798ed3a74fae527}}. This is achieved by conducting a semantic and grammatical ana... | d | 5478b096c654b453774e17a5d8d4c93d |
where {{formula:b6925347-7a38-48cb-bf44-dd269d064481}} 's are the Darboux coordinates of {{cite:36bd53ba4cb85531c7a894ed3f985432b4b3c278}}.
The semi-classical analysis on the conjectured form of {{formula:c74a0476-cb0e-4097-8765-6756f5ddc972}}
would be interesting and illuminating as in Ref. {{cite:7be463e1791be75f67... | d | 793450c4f9947c50611507eed4996b50 |
LDL on Discrete Datasets:
We evaluate LDL on three datasets–Texas, Purchase, and Location– with discrete-valued features.
In these cases, we used a {{formula:4822c0af-efda-4b72-bf55-224a18972106}} noise to generate perturbed variants of samples (Table REF ).
Although using LDL was effective in reducing the value of {{... | d | ed09ca2f6d475508b9a4f7246e957e0f |
Black-box optimisation {{cite:4bb4d250164c9df36993c6c22af60ded05650b69}}, {{cite:40cc01c53d802fd6f456a1c563ceaa9ef77a31d8}} implies that the details of the objective function and its gradient information is unknown during searching optimal solutions. In HPO, hyperparameters can be evaluated on the objective function, b... | m | 9a375b7dbb15cfa5fb6a8d3766cec3d3 |
We report an exhaustive comparative evaluation, comparing with several high performance but low parameters and multi-adds operations methods on five datasets, including FSRCNN {{cite:24d920eea74ac39d0f84d1deb93db2d13ce0d1cf}}, DRRN {{cite:968d9a0d94155cce51a4bfcce0ecf912b5928732}}, FALSR {{cite:4283834e6b0453d1215b1be6... | m | a230211d6ba13d4c10881b648a68047b |
Similar ideas have been introduced to neural networks recently {{cite:c5e8dc4633993347aca8aad10a3c9107e00a4cd8}}, {{cite:63e0009458c9fb28624966c85c13f447befc0aea}}, {{cite:0f5b351b835ecd6e4d8d8fc28658764f551bf765}}, {{cite:16940b580b527a1d200f14c87b976d7ed8b29280}}. In a stochastic thermodynamics setting, the change in... | d | 8441a2af10b7b2a25c824ea54d633592 |
The advent of recent blockchain technologies brings opportunities to overcome the above challenges of services computing. Blockchain was originally designed for digital currencies such as Bitcoin {{cite:1b7c63cb6202ee43fe20654d92b8d3b03c537181}} and Ethereum {{cite:2a73d0d74d63d3f48f8f333b5b4a887589ee5def}}. Thanks to ... | i | 140ef13e001d9232b7fab1921832a4fe |
Numerous studies have been proposed to address the problem of shape effects on the transport of particles in the continuum regime. From the pioneering theoretical work of Oberbeck {{cite:a338718a01afc3462ffa1a654b51efe890e5fbd6}} and Jeffery {{cite:3c76c9216e76308b4d0235c0b422deb78e009eac}}, who firstly investigated th... | i | aaed6186a46452a504c54fed83c86b8b |
In our evaluation, we assume that the query can include the target (e.g., individual {{formula:f1261277-9ac7-4c15-979a-6ebd3fac3674}} j{{formula:430ac581-5677-4b91-a500-9cbbf867b2a6}} ) with 1) a direct family member, 2) multiple family members, or 3) multiple family members, and other unrelated individuals. We compare... | r | bf80be5f894e3f29c79da580ff56301f |
Machine learning (ML) methods are now being deployed for decision-making in complex domains such as loan approvals and criminal justice.
In many cases, an available ML-based policy may not generalize to situations not encountered during training. In practice, it may be safer to defer to a human expert when using the po... | i | 2cd69a12f5db1083e30061528711ad3a |
We applied the eigendecomposition-based standard DMD algorithm {{cite:c5fd208efe075c2491bfc0c5d364a53b4631eb04}}, supervised DMD ({{cite:f6c110979e63b23788658895d19f5c0c2e3eb5e9}}; we review it in related), and the proposed discriminant DMD to the synthetic dataset.
Each method was set so that it would compute a dynami... | r | 8a2155075d67b77fb10398234763d802 |
converge in distribution to the process {{formula:762ec432-c00b-473f-8787-6a35630e0cc4}}
whose generating function is represented by the Fredholm determinant with
the extended Airy kernel {{formula:e2ddb6c3-f743-4c84-acd5-b5e9cea08f91}} {{cite:2522068d0b7a9605a565f18164675c73a54e2de2}}, {{cite:f2ad10651ff148e809c7b86... | i | 8ff310866c530d89cff59c695ece1d13 |
where {{formula:3f6da0e1-0487-40f0-ae08-9bf17192fa97}} represents virtual crystal
and {{formula:5cea6b68-2bbc-4885-8995-2d10104f567e}} is the energy dependent self-energy
determined by the coherent potential approach {{cite:ebe17ecc4c3a4c04bf6ab8e13b50bd54e68fa0c7}},
as the best known theory to estimate effect of all... | r | 06a5b05163af8927b3bdbc01720cd0ae |
where the binary encoder and decoder {{formula:8420d661-251a-4ba4-80e6-7d3aa904ce99}} are chosen optimally such that the average expected length of the binary string is within {{formula:e0debe6c-b6ac-4b1d-a618-3a1385c464c4}} of the entropy per symbol; see {{cite:9fcff637bc42aaacc34b6110945c6835225440f7}}.
| r | cb5146af2d93cde7be079f6d3e5a2ccb |
Rubio de Francia's extrapolation theorem works for spaces of homogeneous type ({{cite:7cc1ae1c2373a930c0f2ae937ccd21113c94fc29}}). The arguments in the proof of {{cite:6016c8e8adeeb0424f346de78f086306e1b65c48}} allow us to deduce that if {{formula:bb643f94-f63c-41af-a997-b569e2c60b3b}} is an {{formula:ea6ca1ce-6475-40... | m | e06eed6349e078999ccb1eb694e08661 |
Through this study, we gain several insights.
We find that normalization layers affect robustness significantly.
As shown in Fig. REF a-1, the better clean AP score the specific normalization layer achieves, so does a better CD.
Seeing such a positive correlation between clean AP and CD is expected, and the same observ... | d | f889c96dc7488a157a0f3f3219f5b24e |
Results from the various SI models show considerable disagreement in the long-term evolution of TSI with estimated changes since the Maunder minimum ranging from 0.7 Wm{{formula:3d5f9d9e-e3f2-4eff-b3b9-0932e8c0fe83}} to 6 Wm{{formula:8e91e6bc-43a4-420a-b6fb-df94c2089d24}} {{cite:a5d64bcc2ca676e619020e0c1aa184dec2f48f... | i | 421cec32e0668f31a457b9e72402f375 |
This section elaborates our proposed BLGCN model and the corresponding HSI
processing framework. First, we preprocess the input HSI raw data with the help
of simple linear iterative cluster (SLIC) algorithm {{cite:43e0b3adcb76941f314c8a6aaafed6b56e3552c7}}, and
construct feature matrix and adjacency matrix. After that,... | m | 1b72edd1d99b04468656e7d25724947b |
A similar idea was recently pursued in {{cite:e5d49a1173fa082972dfb1dc36862a29c59886c2}} for the task of dense pose prediction {{cite:0fbaa1654bdbaf00c39358a5931f74cc2569c5b9}}.
Just like 2D pose prediction estimates the location of a small number of distinctive object landmarks, dense pose estimation does so for a con... | i | 1022f6ec481cfd2cbd54bed622af20bd |
The measured angles of a frequency-dependent {{formula:6c5ae8c6-2ecb-44cf-bb47-2953e70ee833}} for {{formula:06196db1-df10-46a6-b779-2d61ac930233}} GHz are shown in Fig. REF as a function of the fractional sky coverage {{formula:e8fe7d59-54a3-433f-bf56-b60f3b572913}} . The upper panel shows the probability distributi... | r | 9d5eef4dc8d8feb95947132dba84b1f8 |
Now we present some details of the training and validation for the following four numerical tests. In the training process, all the parameters in the neural network are first randomly initialized from the uniform distribution in the interval {{formula:352f945f-d9b6-4584-80ee-b866165cdfa0}} . Then, we update the paramet... | r | 1e702232fb3a35370fd660e6af7612cd |
Repeated cross validation is not the only technique for evaluating candidate models.
For instance, the method of stability selection described by {{cite:f168851f2389ec9fffc8319c0a13361b9e3bf4a7}} is attractive for its theoretical finite-sample guarantees in controlling family-wise errors.
Alternatively, selecting featu... | d | e0a4aaa62dd50e3ea7be23446fc11c56 |
Interval Censoring.
We have made the “no gap” assumption in the current paper to focus on the right censoring problem for simplicity. However, in practice, it is possible that there might be gaps between the clinical trial and observational follow-up dataset. Thus, to fully deal with the problem, we need to extend our... | d | 4814947c852a030a6264c52b28a59bb4 |
This kind of methods have as aim to compress an image losing the several information starting from reducing the color space like chroma subsampling method and any Transform coding which belongs an important transform such as Discrete Cosine Transform {{cite:acde3e6fe73f4e3c9412a9369630933e2b795868}}.
| m | d776b09de989d34fd3cfc8c3631ef633 |
Figure 2(a) provides an UMAP visualisation {{cite:8ae5a3b49352049b45dba44178459c764f06649e}} which illustrates the class separability achieved using only the three most discriminant dimensions (umap1 to umap3) obtained after the dimensionality reduction of the HSI-LBP feature space. In Fig. 2(b) it is noticeable that t... | r | 25d0267b2e78cbf4dca6f24a47440227 |
Broader Impact.
Like most self-supervised approaches, our approach is data hungry and trained using a large amount of unlabeled data collected from the Internet. Our model in its current form is prone to learning and amplifying the biases present in the dataset, especially if the dataset in question is not carefully cu... | d | c38743e6561978930ad1bc3017a269fc |
We initially carried out first principles calculations using the generalized
gradient approximation (GGA){{cite:b6ede9e9b2444e6ce2e2a36694fbed1b32128a86}} for exchange and correlation,
which is implemented in the all-electron full-potential code wien2k {{cite:af9efe02df0afb709153f3879a5e686fcbfe4c8b}}.
The results for ... | m | b8cba1902642bd89e7044d09fcad30fb |
For each algorithm, {{formula:db677d05-10ad-4639-8732-29a84b2c0131}} is equal to PMI or a scaled log of {{formula:31437182-f4eb-4d7f-87c7-73ed1a334c82}} . Yet, the choice of {{formula:9a2a4e58-7df9-4e28-a724-9b48ec59f6a2}} in combination with {{formula:261658fc-d364-4ca9-9d01-fbd57c89cb07}} provides that every model... | d | 3e5692b730d79d4fa372e3b90ccd9d9c |
The Hölder family contains a large class of smooth functions, and has been widely adopted in existing nonparametric statistics literature for various problems {{cite:e1669cbee2eb14ea68bbb54ff0977c1e64ec37ba}}, {{cite:7c5e0e88d362ad0bb8c696d729148cbcfddd0ad3}}, {{cite:b652046da99324bbb53a3be5346f1aaefcd418c0}}. For MDP,... | r | bed6985695c5ff25b872a350c7765f63 |
In this paper, we address the above challenges by proposing a representation learning framework with multi-channel feature exchange for aligning incomplete knowledge graphs from different domains. To capture the multi-domain nature of KG entities, we develop a graph attention convolutional network that can combine the ... | i | 8e940c3280dccd9deb8c8bd71aaa3d08 |
The pre-trained language model is the uncased base BERT from Huggingface's Transformers package {{cite:234720b5cfaafbe1516db22af882b76ada68ffd1}} with an embedding dimension of {{formula:c805a2b0-f07e-4630-9f9a-68709940d549}} . The pre-trained word embedding layer is the cased Common Crawl version of GloVE, which has a... | m | 77367bde06d5e2ec8e9c5ce3b884265b |
The adversarial attack to speaker identification aims to make an identification system wrongly recognize the adversarial voice of a source speaker as a targeted imposter speaker, where the adversarial voice, a.k.a. adversarial example, is produced by adding human-imperceptible noise to the speech of the source speaker.... | i | 73f57103d61439da44c02b62a6bbdd96 |
We present some recent tasks on the physical processes dominated by the magnetic field.
Magnetic reconnection can be calculated as a traditional megnetohydrodynamics (MHD) process. Turbulent reconnection was firstly mentioned by {{cite:f8a181d0b7261f9b59d703fe8be640052895bd6d}}, and it was applied to the relativistic p... | d | 4abddfb9bea319a9214e242086a19ff4 |
Patch-wise weighted sum: Our fusion method uses attention mechanism also utilized in GANimation {{cite:2912ee748d8c6c225630220bdfa3891308d4788d}}.
Inside the fusion unit, convolution with shared weights is applied to each of {{formula:50414d78-9f66-4d53-b194-bc1fd4f14db0}} warped features and outputs single channel ... | m | df092fb32b674ac4efcdb33f48108e44 |
Coupling two normal leads to a superconductor can give rise to non-local transport processes directly involving both leads.
Two opposite-spin electrons from a Cooper pair in the superconductor can be split into the leads via a process known as Cooper pair splitting (CPS).
The dominant transport mechanism that gives ris... | i | 29eeffddf46d2214ec4b0f04ed02a26d |
I will soon start from the beginning and define a matroid and its Orlik-Solomon algebra and holonomy Lie algebra, but first I will give some background from topology and cohomology. A (central) hyperplane arrangement is a finite number of subspaces of codimension one in a finite dimensional vector space over {{formula... | i | 3b7e18746a7f03abc0052b562f5f51e1 |
A novel method is proposed to tackle the issues in modelling cognitive load, as discussed in the previous sections, followed by an empirical study to validate such a method.
Contrary to all the existing methods of cognitive load modeling, the method proposed here is self-supervised {{cite:6e88150146082c7d213ce5dc6ca2b9... | m | 0b87f5f428181332989f669079c46126 |
Large-scale deep neural network models have an extraordinary capacity to generate linguistic continuations of natural language prompts {{cite:0b2aedfe359f7a4530267acc4ad8fd6ea2bd0812}}, {{cite:a5e69ec46191a1228945073b63bf5790f836b32b}}.
The models provide the probability of words given a context captured by preceded se... | d | f4a53c8d5b40afb86e002d38baba0b6b |
UNet {{cite:cbe80cb20e8ce026453e9a236e53229ef86028b3}} was originally proposed for medical image segmentation. We use a variant that adds residual connections in each convolution block as the backbone network in this work. Details of the backbone network is given in the Supplementary Material.
| m | 4bf396cc82dcc63fef9b9538aec80b96 |
We propose EdiTTS, a score-based speech editing framework that enables phoneme-level editing of pitch and audio content. EdiTTS does not require any additional data, training, or architectural modifications to the model. Unlike score-based image editing methods, which directly modify the input, EdiTTS induces editing b... | i | 640657a9fc09774af067152476b3b6d4 |
While the population synthesis models are often referred to as theoretical models, it might be more
reasonable to consider them to be methods that attempt to interpret observational constraints in terms
of the many complicated physical processes that are thought to be involved in the formation of
planets. As mentioned ... | d | 9e6038d0477fef3d2e693d3bec76e553 |
Remark 1.2 It is well-known (see {{cite:f4eb4c05167a7866b620bf866f22c2bcbd6a8815}}) that convergence in {{formula:6e2c7369-4f88-408b-aaf4-9d147931ce7f}} does indeed entail pointwise convergence in the case of
Reproducing Kernel Hilbert Spaces (RKHS). Because the space of spherical
eigenfunctions is indeed a RKHS, agai... | r | ad81fd7359cf696daa296f535a47a28d |
We compared our proposed framework with two recent methods designed for multiple OAR segmentation from head and neck images: FocusNet {{cite:a22c78bf72a1305b5da6a151f691dcbd2e99c459}} that is an end-to-end two-stage CNN adopting a segmentation-by-detection strategy, and 3D SepNet {{cite:ddb96b45e379fad077578d971c9c92ba... | m | 316e5bd3315c938a502ab168f517d859 |
With the rapid development of deep learning in the last decade, deep neural networks (DNNs) have become the predominant models in various fields, including computer vision, natural language processing (NLP), etc. However, for a long time till today, DNNs have always been criticized as being excessively large to be depl... | i | ecad4545b2fdf1f3224eb130e3ac74db |
As a general framework, Ask-RFFs also covers symmetric kernels, including PD and indefinite ones. In that case,
the complex measures reduce to real signed measures, i.e., {{formula:7602371c-0ae4-456b-9ffd-e9f260e4da64}} .
Then the proposed AsK-RFF is equivalent to that in {{cite:d9b2baa8dfda69de43ec93d38eba8644090f3792... | m | c677ea0eb7d5263a9901b31f659c94e6 |
Our results are in line with {{cite:6580049c0ed21f141160bc4660564cfedf2d2e4a}}, who showed the improved convergence of Disc-Opt over the Opt-Disc approach on image classification tasks.
Here, we show similar properties for time-series regression and CNFs using several numerical examples.
These applications differ from ... | d | f1077f44dc6994b811fecab3f2bba02c |
{{formula:412e72e8-2906-4a8b-a0fd-d816d03803c4}} Doradus shows an excellent agreement between the frequencies found in photometry and spectroscopy. This has not always been the case for previously studied
{{formula:a195549d-b283-4165-abef-2616863bd733}} Dor
stars (e.g. {{cite:36a859d8a6e3cf9f96a4d2a23c741eb02847df7c}... | d | 0452ae6e569fa493f52aee9066f689ac |
Then we confirmed the upper-bounds performance of the segmenter on the target domain and report it as Seg-CT. Generally, these results are comparable to the standard U-Net {{cite:f9bad2193df8dc43181c7f069ce31f0374b333c6}} and cascaded-FCN {{cite:5e7561e09a9004bbf8c29ad388ceb08fd2b7895b}} methods. Furthermore, comparing... | r | 1944ff4fc24c407ab2a310371b7349c9 |
To alleviate the exponential computation and memory requirements of training GCNs with multiple graph convolutional layers, and correspondingly improve their scalability, sampling-based methods, such as node-wise sampling {{cite:2a5680463024b1c0c8ffa8e4c882388845e443d8}}, {{cite:f0c7b4782c9ef3d5cf8ec24a18ea0bea8f0ee2d4... | i | 28c952f6b82a7f0a3bc32ffe66babc27 |
Here, we only investigated outlier explanation for tabular data. Applying SPNs to the closely related task of image anomaly localization {{cite:ad599b003d7488381ae4e7d375e60c44292cb790}} is a possible next step.
For this task, SPNs suitable for images (like Deep Convolutional SPNs {{cite:17c94291dd4a0496e79d9dc3e2702b7... | d | a95b7c3eae2ba586e46f3f914b071f35 |
Video analysis. Individual cells were cropped from the acquired video data using the cell wall PI signal using Fiji (ImageJ) {{cite:d41c3a7af032bc7c8b9f60f2d48aea42a4b1925b}}. The size of each video was scaled to the universal length scale 5.0 pixels/{{formula:3efffe63-d7da-49a3-b65f-4bd6d6dd6704}} m. We then extracted... | m | a1e0043e6641dbf9e6a1742ce1c02d37 |
Finally, a very recent constraint comes from the measure of the radius of the massive pulsar PSR J0740+6620 made by the NICER x-ray telescope. This is related to how squeezable are the neutron stars and allows us to put a inferior limit to the radius of a two solar mass object. A inferior bound of 11.4 km, 12.2 km, 11.... | r | 3630ac532c2104361a45a4ae9b08a79c |
This approach has been studied in various previous works {{cite:0c7abf17a063f37bba4d46af4b0daf0ff9caf870}}, {{cite:73fbb8d3c1419a8d4b6a2baeef1d1a94884350dc}}, {{cite:86e1c3d91e1cdfb0e5a8b3ef22107c52ddd11f9f}}, {{cite:3556c298932284eda93454d3ce7a5f153abb88e7}}, {{cite:db2ada80754a9991d29797df9dcce59faae0232b}}, {{cite:d... | i | e9e68d3ec139444050a4a60b6d90297b |
As other types of transfer learning approaches typically require a large dataset for knowledge transfer (many based on deep neural
networks {{cite:dda7a2430a761ea1899553a865e811fe496004e1}}), it is not feasible
in our case as we have TMA images from many other cancer types but each with only a small sample.
{{figure:a6... | m | 68ad69c70003b2cb37998202f938402b |
In general, to constrain the parameter spaces of the present models, we have modified the codes proposed in the MCMC method {{cite:b2a5e4892b3d74e1516a74d98ad8a37754aac498}}.
There are three statistical analyses that we have done to calculate the best-fit parameters: The first was done on a non-interacting model so-cal... | m | 5254ffed1a4fde67db20ea669f87d66c |
Even though a direct attempt at generalizing thm:dagnew to all directed graphs fails, one might hope for some analogue of thm:dagnew that does hold more generally.
One interpretation of the above counterexample is that the exact statement of thm:dagnew is not the “right” framework for getting a local-to-global shortest... | r | 5ff155916f1f576d8673588697ea0ed9 |
where {{formula:d3013820-c94e-4e18-83b3-382d51ce3484}} is the original image, {{formula:10c09b78-fd96-46e2-8845-796618ce33a1}} is the final perturbation, and the last summand is a constant term only depending on the size of the image. As {{formula:2a0323e4-db8b-4504-8e09-443fc1f0115e}} perturbs every pixel by a smal... | r | 93b2b8a55bf53c45217262116fdb4ba5 |
We tackle the computational bottleneck of GPR and introduce an ensemble approach in the spirit of the mixture-of-experts method.Alternative ensemble approaches proposed in the literature include the product of GP experts in {{cite:40b1b0c13c120d211cd1f55d080ffa00468b9c41}}, the generalised product of experts in {{cite:... | m | ffcdb0a08ab9409f38ee89caca34c42e |
However, there are optimization scenarios where even zero-order access is unavailable or unreliable. Indeed, studies have shown that it is often easier, faster and involves lesser bias to collect feedback on a relative scale rather than asking for reward/loss feedback on an absolute scale. For example to understand the... | i | 818be16a92c1dd7c9bf0c02452beb7aa |
Compared Methods. We compare our method against 13 cutting-edge competitors, including (1) FPN {{cite:7e0b8abde4786f1d2c798aef808d4dcd242fc728}}, (2) MaskRC {{cite:a7da8f6082ddff02a6530ac96626ed225f38852c}}, (3) PSPNet {{cite:dc6f1eb4555cc6447d07ffd3dc73090e6329189e}}, (4) UNet++ {{cite:e4f770d84e5f5e561e3db5d449d9a75... | m | 05df4082146fc12ce94cde991fc2c961 |
Over the reals, Elekes and Ruzsa observed in {{cite:6298985bbc12d36536a19ae8836fc01f52088551}} that the Szemerédi-Trotter point-line incidence theorem {{cite:96c4f74306b99c0f3f73ca59b462884fe8b08960}} implies
{{formula:a1ba733b-ba74-40f7-8bd0-2e1378b1eeea}}
| d | 57ea835d3d2ee667c464f70a6da3fb04 |
Reflective and Transparent Surface:
Our depth estimation has limitations for reflective and transparent surfaces such as glass or water. An example of these limitations are shown in eqviews (Hill scene), where our method contains ghosting artifacts on the glass window. The Multi-Plane Image (MPI) representation has dem... | d | f7e3318effddbcabf0bde2b5f9907ba6 |
Compared to the existing game-theoretic models for explaining oscillatory behaviors, our pairwise game model does not require three or more species {{cite:6fc847eec4806437a5dd845f5f6f312af91ad34a}}, or seek for other complex mechanisms such as mobility or conformity {{cite:d491026a72460438c65145236501cf70acd2f1da}}, {{... | d | d847bb7d1ed6d69ec159e6ffd0435ab5 |
Paired setting. In the paired setting, we use the Structure Similarity Index Measure (SSIM) {{cite:0783f17182a96a59e252fb2f630a7e10146b56b9}}, the Peak Signal-to-Noise Ratio (PNSR) {{cite:739cd4d455374c17cac0d8015165292807e34ee2}} and the Fréchet Inception Distance(FID) {{cite:9bdb40f5f2344e4bc63963fa9b4912c348c6cb2b}}... | r | b64ac79120268ab20fd35ff3538fcd1d |
Image understanding can be described as the process of automatically analyzing unstructured image data in order to extract knowledge for specific tasks. Automatically assigning images to pre-defined categories (i.e., image categorization) is one important form of image understanding and an area in which we observed sub... | i | 1b0fb9e095b5a23a0292f1f01ba664b4 |
We combine our loss function with open source SOTA methods (FIDT {{cite:93ad20e28063dbbd2c44f9341bb826d6134990c9}} and FDC {{cite:a9e273ed90d023f6409a6628d445c70123b2efd7}}) by using our loss to replace L2 loss in the counting regression of these methods.
For FDC, we reproduce the experiment with ConvNeXtS as the backb... | m | fe4a8a3eb74c322be4c5b62c4c757021 |
Furthermore, we have compared the eRAR with the alleged universal functional form of the RAR (i.e. Eq. (1)), but not the actual distribution of the sRAR (i.e. {{formula:44736e98-c6a2-4ef7-ab8f-ef68b165cf53}} ). In fact, our objective is not going to compare the distributions of the {{formula:7975a71e-e99a-4912-9efd-d11... | d | 5a837fcb3b9b9387a6bc29f6a365cfb6 |
Let {{formula:534ce4af-075d-4bf9-8935-025d97e0c17a}} be a set of parametric components and {{formula:a0d33b7e-1e17-450c-a77f-e16122f581d7}} a mapping. Then, the equivalence problem for FOEIL sentences over {{formula:abb82707-259b-403c-b338-a3287b6b5b36}} w.r.t. {{formula:5a2f7291-37ae-4aac-92d3-d321d53f1a00}} is de... | r | 10e194ee6d50efbcb1b762778119b504 |
The observed vertical patterns of velocity ellipsoid help us to revisit the nature of the disk flaring. We find that the flaring of the disk begins near the solar position, which agrees with the findings of {{cite:8ec926550f0e2a7d02e24f4de6e60b9390e6a745}}. The position where the flaring starts to manifests itself is n... | d | 884d5cd0fc80dff70b80484e0c82693e |
Neuromorphic computers perform computations by emulating the human brain {{cite:0bcfa62de1c01fd9f8d442252609788fd59bfcee}}.
Akin to the human brain, they are extremely energy efficient in performing computations {{cite:1d3fe463d2650c3bcf69a3cb858680070f9a7c3d}}.
For instance, while CPUs and GPUs consume around 70 W and... | i | cbb825ff40d5159382fad26df954175e |
We mention experimentally obtained material parameters of a double-wall
nanotube structure{{cite:40c60af3fcd2fca5c76e811c7867ed495ca90e58}}. Nanotube length is 10nm and the intertube
gap length is 0.3nm. The diameter of a nanotube is 10nm{{cite:bab58dc9323c1bdded3438b49490083a6563f8ef}}. Q factor{{cite:857a268b77ae7c68... | d | 152b84adde3677c88273ea19c82e6d2f |
To intuitively illustrate the topological magnon transport carried by chiral edge states, we choose some unit cells of the kagome lattice strip as a center region and set the rest as two semi-infinite leads in equilibrium at temperatures {{formula:5c48d33a-ef09-49d9-b4be-ad54dc9706d3}} and {{formula:722e5a86-1766-48cf... | m | 97c137c92d8766307b24fd81c96ef8b5 |
Ultrahigh energy cosmic rays and neutrinos are of interest as possible probes of new physics {{cite:ad903cbe9150c72ca839f9bf83db1dfa1d39bbb7}}. In particular, some quantum gravity models predict that Lorentz invariance may be weakly
broken at the very high energies, leading to potentially observable consequences. The p... | i | c327b84dfbb80352f50a6a707945b2c7 |
We remark that there has been a few works that draw attention to the potential problems of widely used graph datasets. Specifically, {{cite:abdf30accb9d74f619e2b2b5d5760fcc9d6fcda1}} observe that even by using simple graph features such as the number of nodes, they could achieve similar classification performance on co... | m | 13d9f3f01c47c479fb77200f21ed004f |
It is well known that including delays within a DE model of population dynamics can lead to major changes to its behaviour, such as causing instability, oscillations, and extinction,
which are not observed in a corresponding ordinary DE model {{cite:a7dbccfcb114f22d99f1cf22d650a53afc651b98}}. The famous Hutchinson equa... | i | f64d2e2b51b8cfb3fb9b5924f1c5fb89 |
Both our misalignment-induced splitting and the slight upturn at low temperatures are consistent with the distortion-based dipolar spin-ice model (d-DSM) {{cite:d0376a2b839fb15b4637c2290ddbe1b9cfecf855}}, which builds upon previous theoretical models {{cite:5ede464c9456e6d95dc308a6932e7a62f4c3202f}}, {{cite:3dc50cead02... | d | c24ae9dc30e4cd4d59afa09d9b5fee18 |
In this section we describe the fitting methodology that
is used in this work to map the EFT parameter space spanned by
the Higgs, diboson, and top quark data.
In addition to results obtained with
the Monte Carlo replica fitting (MCfit) method
presented in Ref. {{cite:f515b9662ac5e86979e90af25c6fcee78d4b0d94}},
now we ... | m | b454bfaaa38444df0dc78bdab3ed34e7 |
Our model is based on a standard framework of firing-rate neural networks {{cite:dc4b2c63215374e1f0babc94840f97b145403303}}.
It consists of {{formula:ebaaf9ba-ffab-4a9c-99eb-e64b564ba685}} recurrently connected neurons, with {{formula:21dda288-3bf9-44f9-928f-72cc84c9c6b3}} the synaptic connection strength from neuron... | r | 7b24b32544f662647e04c1b0492cef1a |
All experiments are performed in POLARIS GEM e2 autonomous vehicle platform shown in REF . It is equipped with Velodyne VLP-16 LiDAR used for localization and mapping, dual NVIDIA RTX 2080Ti GPU for GPU-accelerated edge computing, and drive by wire systems for steering, brake, gear, and acceleration controls. The entir... | r | 8a22729e855cc1867ac792ec09aaa5d9 |
The phases of the minima are dramatically changing in this system. The variations of the pre-whitened light curves indicate that the spotted areas are not stable on the component. In the pre-whitened light curves of the season 2003, two minima are seen separately from each other. In the season 2005, the pre-whitened li... | r | c3766a15d04189b425b08e3e26b4aad4 |
THE discrete cosine transform (DCT) {{cite:8c1cb61fb4ec9ed5dab35b5f674276500f971385}} is one of the most common tools in various signal processing applications.
Among the eight types (I to VIII) of DCT, type II is known to be especially effective for image processing and has been used in many practical applications, su... | i | 9bfbfa11e19637e3cc90976f38879e6b |
To derive low-energy effective Hamiltonians, we performed first-principles calculations based on DFT.{{cite:2cb0443574083a7fd4ffa185c77e9baf9b26a516}}, {{cite:0686e7a873191e476cc9e102977f50d1691275da}}
We used the generalized gradient approximation (GGA) proposed by Perdew, Burke, and Ernzerhof (PBE) as the exchange... | m | 65753d309a1d11d5d5859cdc21d02df9 |
The sideband signal encodes
the position-fluctuations spectrum of the mechanical mode.
At low drive powers, the area of the measured peaks with blue and red pumping (Stokes and Anti-Stokes sidebands) are proportional to {{formula:16619390-2731-4f7f-829f-0be3855365d2}} and {{formula:74bf5ac1-ee50-4146-8187-473be36c5c51... | r | 88066c0e904207ad74d4d704e039c913 |
Direct numerical simulations of SCF satisfying the Navier-Stokes equations were performed recently {{cite:b724e72a70acc3a7365fd57211eef1f2050658dc}}.
Using the equilibrium states obtained from the simulations as seeds, the spiral states with {{formula:659ba04b-1ade-428c-a605-8ec6616ebe33}} , and 2 were solved using the... | r | 56ea6263a4d0419c72abb53d0aaadf8f |
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