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Learning to manipulate objects is a fundamental problem in RL and robotics.
An end-to-end learning approach can explore the reach range of future intelligent robotics.
Recently, researchers have shown an increased interest in visual affordance {{cite:c14c6c0515e46c803bf4ed1f54ba7cebb0f4d8e8}}, {{cite:92fe3510cecfbc29ed... | i | 8371b8f8a0d6cd74cc0f27b36e25c030 |
Human perceive the world through a variety of senses, such as hearing, vision, smelling, and touching. Since the sound and vision are two dominant components, audio visual joint learning has attracted increasing attention in recent years. Audio visual event localization requires a machine to detect the event segment in... | i | b603fbc2a2a6b20bac135f047c6ce9c6 |
The course, in addition to the Java language (version 8), provides an
introduction to UML {{cite:379b582df86ecd9e3b084329f27242341afb5d84}}, design patterns {{cite:3b7e37c6a0eba3ec5aaa096958b3b27bdfb0c3da}} and basic software engineering
practices. It basically follows the indications provided in {{cite:431a6c2b713206e... | i | 876c0a06ad058000fb6ec6cecb642998 |
where {{formula:2cfe2976-2827-4da4-b10d-a4ea78a47df4}} is the affinity matrix, and {{formula:ff041795-aeea-4f71-ac09-c56c96944548}} is the implicit regularization on {{formula:9331bd63-a26d-4b37-9a61-ef604a2bff0c}} to promote a unique and meaningful solution under the assumption of self-expressiveness. According to ... | m | 5c119efe26f826ec4aceb338932f7064 |
Lemma 1 [Lemma 8 in {{cite:ad2a2234f0a1395d2283a88ef838c6ca38a7f9ad}}]
For almost all linearly separable dataset {{formula:d98bc6b1-31ee-4fb2-93ab-9661019b2d51}} , consider any sequence {{formula:95a81d9b-2650-45de-acc7-715d79f4218b}} that minimizes the empirical objective in eq. (REF ), i.e., {{formula:1e29fddc-cd5c... | d | 92d281da7154b0eb4030c8776d82ea67 |
Patched patterns we have discovered bear certain resemblance to coherence-incoherence patterns observed so far in coupled oscillators or coupled excitable systems, but also display considerable differences. In particular, patched patterns are different than bumps {{cite:11c090465f02efeeb313272179079afc747a6073}}, {{cit... | d | 59cfbeabb717ffe44d9bf3214ea52a4a |
The initial codebook {{formula:448cd269-f7a0-4825-8003-83b9f43a135c}} for methods {{cite:128ba63a0fbcb31ae29605137c46aaeab44a5510}}, {{cite:bb4943f0d4083b68638c7b859d558d2d82c65360}} are computed by
the fuzzy C-means method {{cite:3bf6b59481173e0f1a60611932775cac826d2df6}} with 100 iteration steps, and the thresholds ... | r | 60b132650bfbe5ff27ce17a7612c599e |
Explainability and biomarker discovery.
In order to determine the regions of interest in the brain that influence the prediction most, we extracted for each of the four tasks the learned weights of the RegGNN using the best-performing sample selection method.
In Fig. REF , we show the regions of interest with the 3 hig... | r | 5f4a6d67bc1998d59e1156257201efd2 |
Given a gradient flow, which is a path {{formula:7f943628-c279-4bce-b99d-8dccec2b40d8}} satisfying the gradient flow equation, {{formula:eaf2e2a4-a0d8-4dd8-94da-6bc7424b4f17}} are critical points. Moreover, critical points carry important effect to the rate of the gradient flow. Namely, when the flow {{formula:2b9a1a... | d | 505a896751f28ec72690cd2e1c4c5a6a |
[leftmargin=*,topsep=0pt,itemsep=5pt,parsep=0pt]
Uncertainty: select closest example to current hyperplane estimate (i.e. {{formula:fb89e3fc-b033-4e1a-a460-23e1514be0e5}} ) at cost {{formula:26e548d9-6e4f-4448-8044-b9d78228d1a8}} . The action of Uncertainty sampling is comparable to that of the first term in (REF ).
R... | m | 6277f7a8176160119f9dc0e636328b99 |
+ ShaekDrop + PBA {{cite:2354de1c84473cb3784fbd98c6629a81cbf273a3}} {{formula:9b354b7f-917b-4cb5-b9bd-719380d365a5}} {{formula:52bf9291-6289-41a4-861d-9fa40ae0ef6c}} - {{formula:14ddc6cd-0593-4b06-928e-4a8e0b73e52e}}
| r | 52084d46209f8e2561cdbbf7df9ce3b4 |
All training was done using the hyperparameters: {{formula:d067db59-71f7-4845-bf3a-4a365fbab00c}} , {{formula:71f82d38-ad3b-4c22-95ab-103f74f9979f}} , {{formula:c0c1f4f5-d67a-4e8f-b974-9c92e0545ab8}} , {{formula:0df29663-f4d3-487f-8cb4-f88c610c0ef3}} , {{formula:bb5b85a1-51a9-4a43-a537-f05899522764}} , {{formula:b0f2db... | r | 60f98eb4a40c9a436f887104f0ceab7d |
There are two benefits of unguided methods. First,
unguided methods are more robust to environments with light or weather changes since they only take sparse depth maps as inputs. Moreover, for the same reason, they are more computationally efficient.
However, unguided methods show inferior performance due to the lack ... | m | e56ee888edd492c51b24b27e59c6e9d4 |
To extract such information from the measured GW signals, one requires template waveforms
that have to be compared with the observational data using a Bayesian framework {{cite:a077ba70a2037928e89c788d0b31d693f8444847}}
to estimate the intrinsic binary properties such as masses, spins, or deformability, and
extrinsic p... | i | 5ed781d5008919467a32b4f1ebb79036 |
Incongruous Meta-learning.
When fine-tuning the task-specific optimizee variable {{formula:49cc5492-4cff-4a49-8ffb-3c3383eaeaf3}} by {{formula:b4cc8883-df9d-46d1-8945-5de72868d736}} (Algorithm REF , Step 6), we can use an invariant RNN architecture
to tolerate the task-specific variations in the dimensions of optimiz... | m | ec385c74cb89dfca8d11aa8b6349f7fc |
There are some basic laws to characterize the quantum world in compliance with quantum mechanics, of which the most well-known is the uncertainty
relation. The fundamental uncertainty relation is called the Heisenberg uncertainty principle with regard to the position {{formula:7a785690-c36e-405d-8c7e-b67913b94052}} an... | i | 5301972a14af78ee1893542583565b30 |
(see {{cite:e8541d79ed8afab441af1a28ef3f9216075e5565}}).
| r | bc89b3792759585a254a9b6170237b59 |
The optimal/suboptimal solution: for the SINR balancing problem, the solution is obtained by using the iterative algorithm proposed in {{cite:1dad981bd09d22a27879cf73f6f69b8737882ff4}}; for the sum rate maximization problem, we consider the WMMSE solution in {{cite:23b24d7aa022e7b011e5a2d7e591bc524a1c44b2}}, which is ... | r | 0cbeeb353c691734c1234412a90aab2b |
To solve the bubble wall velocity,
we firstly need to know the bubble dynamics which is quantified by the equation of motion (EOM) of the background field.
Based on WKB approximation we can derive the EOM of the background field{{cite:e8536e9d7e8b3614d4a3d1bacf2b9828cdc6c9ce}}, {{cite:d45501eaecc2ed76edbf3f3280e007b22f... | m | a8fd3f68f39c68e0ca6213220a48730c |
The final goal of this paper is to show that the evaluation procedure must be adapted from how it is currently performed.
First, many evaluation protocols require to provide separate results for each protocol, and we have done the same mistake in our previous evaluation {{cite:bec66c9eb8516995e40c0a82d24be457832a1758}}... | d | b9a7d9a7dbc54837658e68200a42e6af |
We have also presented a specific superspace term that can induce Majorana
gaugini masses on a quintessence background and studied few of its properties.
We have seen that in the new-minimal formulation such term takes a very simple form
and we have argued that it does not lead to higher derivatives
(or higher order au... | d | c8ab2858d9ff2e78356141fa30f60161 |
In Fig. REF , we study the impact of the IRS location on the BER of the IRS symbols for {{formula:f3e2a8f1-93c0-46ff-84db-c95782565d04}} . Specifically, we study the BERs obtained with the considered schemes versus the IRS's horizontal location ({{formula:94ab99db-ed81-4a59-9dc3-5a71432b4e39}} -coordinate), ranging fro... | r | d943e1b98cd161a8444600ebc5bb986c |
We note that our work does not determine whether internal deformation {{cite:ca377757c9d53f931d1871dbaeba3650b33f5719}}, {{cite:7c3346dff99d3dadf868225f1fc73db12965ed51}}, {{cite:009cdd55e1c3d2bd1926d9557673f81ffbbf50e9}}, {{cite:f2cba6199ea35f1b31d3a0f8ba60d9eeade93a2a}} or surface mass movement without internal defor... | d | 3d0509c7646485d3b4b199f955a3ceba |
First, we observe that the fully unsupervised vecmap model, despite being the most robust fully unsupervised method at present, fails to produce a meaningful cross-lingual word vector space for a large number of language pairs (see the bottom triangle of Table REF ): many correlation scores are in fact no-correlation r... | r | 7cf891d8ebcc5d4899adf2948912bd6a |
In particular, BNN {{cite:b15c1d61eae5fc6f1af04dfa263dd99c395e17d1}} directly unitize the Straight-Through-Estimator in training stage to calculate the gradient of weights and activations as
{{formula:c63c7021-e80c-445a-83fe-53e1148dd1fb}}
| d | ef9af2ecf3feb69f8178cb8e22e04afc |
Per literature, a system of differential equations for Susceptible-Infected-Removed (SIR) sequences is a typical mathematical epidemiological model for COVID-19 forecasting.{{cite:8f3a68c2e774a1289d773ecc5bbc014b9035cad3}}, {{cite:737919bc263796873033486e151e2c066a06d598}}, {{cite:847589df97cbebeb5d2a0832e2930880a4f1a3... | i | 856e91bf2c8183ec18b0f1b501125711 |
IGMs can create multiple views of images via their latent transformations {{cite:e08caa0b1ee82fd7e7692146ec613e9dd7397e67}}, making them useful for contrastive multi-view learning. In this section, we study the effectiveness of contrastive methods for learning representations from IGMs.
| m | efe679433bf7cad91473adf944524abd |
In this manuscript, for the QAH effect, we consider another method of creating
quasi-periodicity, by coupling two QAH layers with arbitrary ratios of
lattice constants. Experimentally, this can be realized by using state-of-the-art
fabrication technologies of topological hetero-structures{{cite:cc1af37f5720f7652c5187eb... | i | 436401efeb4928e03b5bdc8a8d05e30f |
The window method has been presented for the first time in Ref. {{cite:e8f019e75657e80df24f3e575accb011a1cd8c0a}} as a tool to improve the accuracy of the HVP by supplanting the dispersive results based on R-ratio measurements {{cite:c6d1c894adf7d56d19eec50f8a9526adb9251d18}}, {{cite:89c0fe5f3014f7d4c500af891f34f61e4a3... | m | b9b0b6def99ce1ca117eb5a0e8cf652e |
Avoiding annotations of training images has a potential to further overcome the difficulty and high cost of acquiring a large annotated training set. As an attempt towards this goal, unsupervised cross-modality adaptation methods {{cite:bf9abeebd880d9ca508df7c6c4ed4c467fbdeade}}, {{cite:549fbe85467c25d8f18048d55df304de... | i | 300b26484fb705fce8f67595dd32be53 |
L-DAMP {{cite:fca8d8c162408cfcca2677b9361eb43233dca2f2}}, {{cite:845aa6be3a0dcad610ed95d7f17c291fd66b4c17}}: This represents a powerful deep learning algorithm that performs model unrolling. We use a denoising convolutional neural network (DnCNN) {{cite:2cb932ae5aeb614afbf311d4ab59930aa4327f48}} backbone, which is int... | r | 62c7005de70b885fed9787a684cd2e62 |
Before 2015, researchers usually model a specific texture model to represent a style. Because this modeling method is non-parametric, it requires professional researchers to work manually, which is time-consuming and low-efficient. Moreover, each style model is independent of each other, restricting it from practical a... | i | 4f01b55cfb60b0e7de995642636d45cb |
where {{formula:c2ae95d9-1943-46b2-8700-241b39c66355}} denotes the regular representation from {{cite:f8d843e14c51201f8c2ea14e6c59ccf7aa829e1d}} (in that definition, this map is called {{formula:7fee38ee-9f78-4106-a4ab-641502b5b073}} , but we have changed its name to avoid confusion with the {{formula:896fe919-75a2-4a... | r | fbad272b98b1a2f051a67478ee5508df |
Approximating an Ising Hamiltonian's ground states can be achieved by applying simulated annealing based on a Markov chain Monte Carlo spin-flip dynamics. The most usual example consists of considering a time-inhomogeneous Markov chain based on a single spin-flip dynamics (such as the Glauber or Metropolis dynamics {{c... | i | aa61c949462168d809a5ceda7594ac39 |
So far as we know, rare research work explores the conflict between the literal and deep sentiment.
Existing methods for sarcasm recognition focus on the sentiment contradiction reflected in word pairs or phrase pairs that appear in the sentence explicitly.
{{cite:a73da0a9d232968bd371a928fe925d83bfb19f01}} propose a fe... | i | 551393c1de5256f01057597f08b864d8 |
Although GS98M was chosen as the best SSM with high metal abundances, the value of {{formula:fee7207e-2fc4-469b-9b95-135632b713af}} of GS98M
is slightly larger than the detected value of {{formula:959ee21c-0afd-48a9-be88-1e6f7190f111}} cm{{formula:ed3e2518-c8f3-47cf-a736-bd31ced48e62}} s{{formula:599152ca-60ca-4774-... | d | 07724a1e0b3d0fdf90460e5fe437363a |
The implementation is done using an Ubuntu 20.04.4 LTS operating system with an Intel(R) Core (TM) i7-8700 CPU @ 3.20GHZ X 12 cores and 16 GB of RAM. The language used is Python and is executed on a jupyter notebook. Scikit-learn's {{cite:ef9a2406534b1a42fca18dcbefa35f98ce4fe6c8}} Bayesian Gaussian Mixture Model and Ge... | r | 0a901d513268f2444e0ad0986c60220e |
The current architecture uses non-linear functions as in the conventional neural networks, which is potentially a universal approximator and the property is supported by the non-linear functions and stacking of many layers as in other deep learning architectures
{{cite:47081da6bb60e51cc91cfb00af48480613824e92}}, {{cite... | d | c2fe9b7b31c10fec0488b709da3e571d |
While in small systems achieving the maximum {{formula:e18db193-989b-4a9a-8b6b-f4e5588a2326}} requires fine-tuning of {{formula:960e304f-e372-4028-a7bf-e57a88799d89}} to locate a resonance, for larger {{formula:d2a1c80c-3cdb-4956-b0e3-090b7c1f3b38}} this constraint is rapidly removed due to the exponentially increas... | r | 42a6cd400165578308db53f7d9e26cd7 |
Orthonormal Directions: While constraining the directions to be orthonormal still leads to the same subset of interpretable directions being discovered, their quality suffers. This aligns with the observations of Voynov and Babenko {{cite:ad2858310f85b85812d425626d50f70f2c2739b5}}. However, their results show that some... | d | 5c8406b19efd0a27cc00823df0afa3ec |
Table REF
reports the results of semantic segmentation on ADE20K.
The segmentation results
are from the corresponding paper.
We also report the
results
of object detection
and instance segmentation
for MAE
under
the Cascaded Mask R-CNN framework {{cite:75b3a1780080f5d2440eb591fd6534ed056667d6}}.
This is different from... | m | f017d7b1d6cc33767efe25c18d512d8d |
As we shall see in Section , nearly all variance reduction approaches in RL employing the general framework of Algorithm REF , use an importance sampling technique. This could significantly degrade the performance of the approach as the gradient estimates depend heavily on these weights {{cite:97fc2a5e5205bf71efb3fb3ef... | m | ec0a5f05ae02c8008d38163f0bd96728 |
In this section, we show the numerical results using the annealing schedules of transverse and longitudinal fields as defined in Sec..
First, we consider the annealing schedules as {{formula:7c3a31ae-fd66-4ba2-a16f-9a8c2d53ebfc}} and {{formula:dc0a98e6-399e-4ee5-8ec7-481edc936958}} where the value of {{formula:a17fbc... | r | d31ba50152763327551bba1c646e933e |
Markov chain Monte Carlo (MCMC) methods are widely used algorithms for
drawing samples from complicated multidimensional probability
distributions. For example, in Bayesian analysis
{{cite:a78ef273d294f08ce2f224e9ecbf1fe31b66e076}}, we are often interested in
computing the posterior expectation of a function
{{formula:... | m | f5e778708780a4f76d6a9cfe7f59a8f1 |
However, the work presented here does suggest that the late-time deviations from the conventionally considered
Hawking radiation thermal state do contain information that can be used to partially reconstruct the initial state of the BH (see additionally {{cite:4c2d747e54ab73e69c1050f5793ea4e1d5ef5261}}).
Qualitative ev... | d | 401874648c0b78931fbf1addf5659d79 |
(the reader is referred to section 4.3.4 of {{cite:04df636e6fca6863db46ac8a12eab0ccec415e84}} for
more details). Griffiths & Tenenbaum's bridge to Kolmogorov
complexity is only established through this last theoretical result:
replacing {{formula:17de51f8-fad6-43a5-ac80-f3878324eac8}} by {{formula:294e3648-a605-4daa-8... | d | 6b5f79ae1663422ebd798b62c02477f4 |
During the exchange of training experience, the parameters are usually updated along the direction of negative gradient. Without loss of generality, for each positive sample in the base model {{formula:2af0f71e-f9ec-4c65-90dc-a5f425697e58}} , the gradient of cross-entroy {{cite:78fd8cbc23e8850a4d5548da7bfc3f52befbb7ac}... | d | 0bbc1520b295be27fbd940c5c089baea |
Compared with the state-of-the-art textually supervised method GroupViT, our initialized SegCLIP achieves 1.4%, 2.4%, and 5.6% gains on the VOC, Context, and COCO, respectively. We also conduct experiments for GroupViT on CC and COCO datasets for a fair comparison. Our SegCLIP trained from scratch achieves 5.2%, 4.3%, ... | m | 43e49e5445de9710bba74fc36de6dadb |
Recently, {{cite:dcfc6cbc2d3b7ce6f7b787f695444bf0a2c3c851}} have shown that there is a strong connection between the low-diversity problem and what they call model over-confidence following {{cite:278b6391f9c92fe0455bd5b5c7a5057790d001f4}}, the phenomenon that a model incorrectly assigns most probability to only a few ... | i | 77af2a52173220d12fd17c71b1568c2d |
In this section, we evaluate our proposed calibration methods for the tasks of object detection, instance segmentation and semantic segmentation using pretrained neural networks. For calibration evaluation, we use the MS COCO validation dataset {{cite:5d54b93b05a101d0651632126a286f0e73275688}} consisting of 5,000 image... | d | d5dfc10cdaff9153010d11dc17bca654 |
Tree based algorithm is a common choice in decision making studies{{cite:8645927d830de7447761ead83f2e1c7fe7a45233}}, {{cite:96e520e4ac9255dfa6f17d4e95c2ff45cd32401f}}, {{cite:6e8bd4b99161f87625138145e345277e9172ff46}}, {{cite:d73dd4ff4a26dbd862d9a266d617cd0a025d5b7b}}. A decision tree{{cite:0377a5d6f9bda5d6950d8d12c83f... | m | b87fa39fcfcc4ecdbd2e7bf935a2f94a |
where {{formula:631fd33b-c4e4-462f-ba5b-ae2634e5c9a6}} follows from {{cite:7f9bab7983f48286778d8a4390ffadb398d4d8f9}}, {{formula:35403eac-1f50-4a99-b54c-6962977cb670}} follows from the log sum inequality {{cite:ebee5d0111ac11b1a5f036f57a00564e668cc5ec}} and {{formula:6eb6fe5c-0f12-44e6-b579-fdcffc7d22d0}} follows f... | r | 0f1adb07a8a96f01989f256eef29c5b2 |
The causal diamond method is discussed in Ref. {{cite:963fffa6bfe2b7ed9f97ae09a2ee979e93e908c5}} as the basis to obtain the field equation of Serrano-Liska gravity theory, whose entropy formula is given by
{{formula:d37b06e3-daf7-43d6-a25a-c2a08c34b711}}
| r | a291a659849f769f5089e2931d46b465 |
To the best of our knowledge, there is no report yet on the online training of spiking RNN with e-prop learning rule based on realistic PCM synapse models.
Our work compares several previously developed methods that are designed to cope with memristor non-idealities and demonstrates that accumulating gradients allows m... | d | 6903158f3aaacae071d3fab61f53bff1 |
In our findings we have exhibited that the M-SGD error is approximately Gaussian irrespective of the distribution of the weights used in the problem as long as the number of samples and the number of minibatch is large. This helps practitioners comprehend that the dynamics of the M-SGD algorithm is very similar to... | d | 3824a65ad2487c9add517d69e7bb145b |
Both studies show that the presence of embedded clumps is expected in clusters born from massive molecular clouds, and that they can easily survive until the stars explode as supernovae.
We also need to estimate the rate of cloud evaporation required to refill the gas and reproduce the masses in the observed shell. Fro... | d | 74eaf96b1f2eb8db375718ec7159ff54 |
In this section we provide an overview of the population-based policy gradient method described in Section 6 of William's REINFORCE {{cite:cb61698e7e5575ff9f55bcb48e1f4ee25d3d4f56}} paper for learning a parameter vector {{formula:c656fbfe-4af5-4da5-a5f5-da5222d3a13b}} in a reinforcement learning environment. In this a... | m | 6f8c182773ba56e1d656db5f976bdfad |
We use RelaySum in the RelaySGD learning algorithm.
We theoretically show that this algorithm is not affected by differences in workers' data distributions.
Compared to other algorithms that have this property {{cite:03bb6dd6998c839bdf3fd8be1905900cab4f7776}}, {{cite:a78c99a702a18a1e3392ffa621e6fb1ed38e966c}}, RelaySGD... | i | 2b2c7a01805fa201ec3cbf8df2309361 |
Most of the notations, functions and identities we use in this paper are standard and their definitions can be found in {{cite:5d0b77729ddbd5d18d7e014b5b93dd764387d691}}. We give below the definitions of some other less popular terms and functions which we use in this paper.
| r | e0a4e55622ccfa3bbe44c91387a44b74 |
The LHC has just restarted for its third run in the spring of 2022, and the need for accurate fast simulation at the LHC is ever more urgent. Simulation of calorimeter showers with Geant4{{cite:305b288372a30bc3b8d1b53542b05d98818cc80c}}, {{cite:de983e0e9bb4f3511a419a4c88b00ba0450ae7cd}}, {{cite:77973148287a15d503b1153b... | i | 6e685bcac052869b9bc3a565285d134d |
We find that high-mass Drell-Yan LHC searches into a di-muon final state
provide the most constraining bound
at large values of {{formula:7735a20f-a46b-46d6-ae1b-9233bc944ca8}} , irrespective of the model. The dominant
partonic {{formula:65aa937f-7991-4020-976a-0d4aec1d39ad}}
production processes are shown in Fig. REF... | r | f866ba33c2cc4e1531941bc74af8210d |
In AdS spacetime, there exist the Hawking-Page phase transition between AdS-Schwarzschild black holes at high temperature and thermal AdS gas at low temperature {{cite:c25fa91f80e265b39dc84bc188709c7f4cc4427d}}. This phase transition is first order, which can be considered as liquid/solid phase transition. This transit... | d | 06d6d4163682de10903e7651deda7d70 |
This paper has experimented with the use of a sequential importance resampling (SIR) particle filter (PF) as a means of dynamically incorporating data into a simple agent-based model of a pedestrian system. The results demonstrate that it is possible to use a particle filter to perform dynamic adjustment of the model. ... | d | 92f67c5bd1a0f96492a7afb6393e2c23 |
We think that the reason for the imbalanced performance of the supervised learning model could be the training metric and network architecture.
Since the pre-training metric is large-dataset classification accuracy, the late layers are considered specialized to the pre-trained dataset domain{{cite:e96ea87fa414af9bf376e... | i | 7fc221773d1e17e1c7136d35b28e0122 |
In this paper, to address this challenge, we propose a novel, robust maximum entropy algorithm, stable for a large number of moments, surpassing the limit of previous maximum entropy algorithms {{cite:e1e5ec79c70730aaf8c18fb1b64071d980fe1710}}, {{cite:0130782f6eddd7713a09a50a03caa16c24d5caf6}}, {{cite:59d364d660a8e3070... | i | 565c13d88431ff4eb67b981252d275a7 |
Generating Assistive Information
Additionally, we show {{formula:bf3ce893-2ccf-4d07-8556-31ee50464886}} can be encoded and then used as input for local critics {{formula:d844b3d1-afa5-434b-999a-321b96cec69d}} , as assistive information aiding value factorization. As previous works suggests {{cite:ddc8fbb99b488cd8857d... | m | 7b9f44336b9a320d548e369b0c4ce2c6 |
In the second part of this work, we have used this structure to revisit the static response of the Schwarzschild black hole from a symmetry-based perspective. Following Refs. {{cite:e5c85331fcb185535e8e221edf9e7e1e8a5786f7}}, {{cite:e4b43cdfab39e8f70c07db5885f9158d9669f5dc}}, {{cite:571df1b414dff025f09f6d1dd18ad61ec3e... | d | d9f9e3ce19c4d0ddcf5ad223324b0aa3 |
A noteworthy aspect of conditional gradient algorithms is that they produce solutions which are sparse: each iteration {{formula:5eb630fa-ecb9-4978-a0df-80d32f2a36e9}} of the procedure yields a convex combination of at most {{formula:b3da90c9-41a2-47ac-8530-f206c3760094}} atoms.
This is true of all related algorithms... | i | 1abc86ed1ad16d57a3531f1b910f0efe |
The regular method to classify the holistic ECG signal with deep learning is to design a very deep neural network, like {{cite:b14d82ac4cf0ca39a538b7be0927488dda460d78}}. But the length of ECG signal is set using this method because the dimension of input is constant. And the depth of the neural network should increase... | d | 32b39ae49cd8bf55ec075387b942f9c2 |
The results on ImageCLEF-DA dataset are reported in Table REF . The CDEM method substantially outperforms the comparison methods on most transfer tasks, and with more rooms for improvement. An interpretation is that the three domains in ImageCLEF-DA are visually dissimilar with each other, and are difficult in each dom... | r | cc2e4af48a4eb3ae032dcf146d568c34 |
is
called the
transferred population between the first and last sites of the
chain, and we assume that {{formula:6bb07ba1-5a7a-4044-b89f-9c95dbc50859}} , where
{{formula:ac73cd18-d46f-45fa-90d5-e41a6530f021}} , as in Ref. {{cite:a61e62971081a509e1b9acbe6e8e5e9dab81ec85}}. The
pretty good transfer occurs when
{{formula:... | m | cb59fcd0ca68fa5ad1db4551e6f135ca |
Develop a chromatic variant of Forman's discrete Morse theory {{cite:b3d4b7023ca7809b22d9a64b42fd723cf6f2779d}}.
Two concrete questions are the extension of the collapsibility of the Čech complex to the Alpha complex proved in the uncolored case {{cite:fb98aa3efa562b8084fe7b83b6951ac40451bba6}} and the further collaps... | d | dfca7e26f349213976a97fbb0be2d26d |
One should contrast the above with the Parikh and Wilczek tunnelling method (in standard general relativity) {{cite:ace049ae1776affb07348cfc613f4d4ec132d894}}, which cannot apply for particle production whenever the OMOTS surface is spacelike, because the whole concept of tunnelling only makes sense for a timelike surf... | d | 10915f2bd90eddd3fd9cc31d30cdcfb0 |
Sampling the fine-tuned policy {{formula:10a849b8-6ad6-4e7c-a43c-3ca1d80b096a}} from the Gumbel Softmax distribution allows us to backpropagate from the discrete binary decision samples to the policy network, as the Gumbel Softmax distribution is smooth for {{formula:511cc1ed-2861-49f7-8b1f-f5912985ab90}} and has wel... | m | b5ea8509fcd3ea19824a101532a44283 |
Most recent improvements in imitation learning are based on improving the asymptotic performance of algorithms. In this work we showed a different direction that tackles the problem by directly addressing the mismatch between training and inference without requiring an extra human oracle or adding extra complexity duri... | d | d3812ec8556c8064c101c9c3ddee252c |
In the book by Samek et al.{{cite:0cd88b999aacbd8fd28c3cd13cc20fbe9d3b917a}}, the authors present recent trends in the research in explainable AI and some of the directions for future explorations. They have presented a topology for the various explanations methods like meta-explainers, surrogate/sampling-based, occlus... | m | a5610ed52756624d8e8cc7011a6d49a2 |
In our previous work {{cite:62172815fdee1d19033ac388f1bbd88c514640c0}},
the free parameters {{formula:e78abea7-0ca8-47ab-80fc-5a43a4bf4e10}} in Eq. REF were obtained by a global fitting of the total and differential cross section data of {{formula:76309be3-c783-43a1-9086-ad0d6c04eace}} meson {{cite:f276cbb3e832fc529... | d | d1555b452dcb9876b7d081a1dfc2fff0 |
Probably the most interesting outcome of our analysis is the existences of structures mixing complex and paracomplex structures. As we have demonstrated, these mixed structures arise very naturally from (a pair of) pure spinors of a given real index. Such more general structures are only possible when the signature of ... | d | 0a48692464a7613a128acbaf1bef594c |
Another area for future research is the inclusion of positional information in the GAN models. Currently, our models treat the generation task in a `bag-of-patches' fashion, i.e. ignoring the potentially important spatial context for each patch. By including positional information such as in {{cite:3486eed0eb521cc48aef... | d | dcc8ada913685b93eb958da7ea8adf81 |
In this work, we have considered the complete scattering amplitude of all the channels instead of only logarithmic terms of the {{formula:106af128-46f3-4c49-8916-ec75e59e4dce}} -channel.
And all the thermal masses are included in our numerical calculations.
The contribution of massive Higgs boson is also taken into acc... | d | 84048406598f0118075a1bc7ee9d2ead |
The data we presented seem to support the claim {{cite:bb9fc5c110112d2460ef8d2551227b68e41df78b}} that the mass ejection in this object occurs
in two different ways: a somewhat ubiquitous and steady mass ejection,
with chemical properties of O-rich objects (SiO, SO, SO{{formula:6390332d-3e0c-426c-ac55-7170e279eb6f}} ) ... | d | d9293567487b2e03a05c399e9cbd7994 |
For this ePFA workflow development, we use an unsupervised ML algorithm called NMF{{formula:ba6a6afb-2f59-43a1-a511-2c12b96a62a4}} {{cite:7c6419d3af8aeb2379aa981c5086a82280810106}}, {{cite:15207c4758e1e4607a5da5fd0c99b81a10683f76}} to discover hidden patterns in geothermal datasets.
The NMF{{formula:a99b8ea7-44cc-40c4... | m | 00c555b2d5d6b02fff25ebc1c01a5a35 |
Table 1 shows a comparison of performance between our work against CP-VTON {{cite:26284f4346e416d72c6e13527526490232dae0b6}}, SwapNet {{cite:176a1bb9ca50c7a7164e64ebffce510a2b8e6173}} and SieveNet {{cite:6433d6850a3d2e6609e87b4403f0deca1ae16beb}} on image quality metrics benchmark, IS {{cite:aeef5ec81a25c98d79215b345a3... | r | 9e7107d1aa373ee0f114288ed2262e4e |
The results of this paper indicate the way to observe the Aharonov-Bohm effect for the system confined by the external
potential in phosphorene. For circular quantum rings the Aharonov-Bohm oscillations
can only be observed in the excited part of the spectrum since in the degenerate ground state the electron density fo... | d | c042d7e7792e15ac2d2f23e2f0ff6264 |
Let {{formula:ca2b1b5b-5588-483d-b6d6-4ea6840705c9}} be a numerical semigroup. Since {{formula:dac05655-3cde-46fc-8fb1-1f355a4e5d81}} is finite, there exists the greatest integer not in {{formula:591ce05d-acf0-4119-a097-232b5c4ad4db}} which is called the Frobenius number of {{formula:db75873d-2c4d-4846-9ce5-1a7a203b... | i | d61de8a3faf13781e27c309705ec3269 |
The classical mirror symmetry summarized in Section applies to the so-called (families of) lattice polarized K3 surfaces replacing the Kähler cone with the ample cones {{cite:390fbdc020f7e838c4b182fe56e048f48af68c6c}}. In our case here, we consider a primitive lattice embedding {{formula:f8cfa69c-ce8c-4c18-a1cd-d8282a... | d | fead537a2f93cb2736b2998bfd3c4be4 |
The PhaseCut method {{cite:9d42da6e3fda6a567fb1def847939d68ca067846}} is based on the following minimization formulation for the the input modulus {{formula:d74e31d0-1bf9-4800-b77e-6b3e8ff064b1}} , unknown image {{formula:3c716542-ad31-4de2-acb7-a02b89e62b37}} with unknown phase {{formula:4e68d8e7-6c27-4ada-b7f2-d6327... | m | 7d35bea189950e52563e6956a204a7c3 |
Proposed-full-CSI: The channels are estimated using the proposed DFT-OMP-based
algorithm in Algorithm REF in the first coherence
block.
Proposed-gains: When the angle information estimated in the first
coherence block is fixed, the channels are determined by only estimating
the cascaded channel gains via the LS meth... | r | f93c8cd160f607d43a5cc3ccb02cdae8 |
{{cite:eefc1323ca054b314d5672b36c22195d16a4f998}} proposed a new recipe for quickly using crowdsourcing
to generate new compositional semantic parsing datasets
consisting of question-logical form pairs.
Using this recipe,
they created eight new datasets in small domains consisting of 12602 total
question-answer pairs,
... | r | ea6223da318f57f020dc31b92b267271 |
We then used the generalized Lomb-Scargle
Peridogram {{cite:091a0bef78c560e4a0307fcead7b2d9b40303b2d}}, {{cite:b7743ba8245c67bd704fe00186bcd5bb4216e3cc}}, {{cite:6fc816cbae958444c5f3022c07bd35da0be0cfad}}
as an independent check for the result from the WWZ method.
The LSP method is a common tool in time series analysis... | r | 17aae0167fec108d8e92639cf713f1e2 |
DeepGlobe Land Use Classification Dataset: Table REF shows a quantitative comparison of our method with the baseline for the DeepGlobe Land Cover Classification Dataset {{cite:6408150b45b7a2041eb9975a66db6356154e23c7}}. We report significant performance improvements over the baseline using both entropy and margin sam... | r | e30bb58d8a1056f28199f3cff54a29a7 |
Recent work has shown that policy gradient methods and Q-learning methods are
connected via maximum entropy RL
{{cite:67557aebd8e3430a2f21298387686a6032b89a29}}, {{cite:3b79229a70e9db8c27f1dc9547ca8b84939679f1}}, {{cite:fdef0e1b27ef47cc019f41d03f6aba52e1777bfa}}, {{cite:14351822bc56c6b5a50427b2c08035cf83033c71}}.
One s... | m | 0e2339cfb6add1db5e2657a89bdaa7c8 |
Then for any {{formula:79fb7c67-8442-4f79-86ae-4afd2f980e00}} , the following classical result holds (Theorem 1.5.3 in {{cite:64714a3ec49cd75aa8fb34789c6a6b2be36c1ef9}})
{{formula:f3f5b969-cedc-4ab6-9e1f-9a2d680c75bc}}
| i | 2eb820410a0e9a7142f9b26e4566cf3a |
(i)
Empirical test spaces are closely related to {{formula:5c69f489-e698-4827-9536-f2d0502ca31b}} -embeddings, which have been recently proposed for MOR applications by Balabanov and Nouy in {{cite:3096db8d0032f99f5527db91946479e5d36f8f54}}. In section REF ,
we formally link empirical test spaces for dual norm calculat... | i | 7022a535c3b9a3f531cf6f30d3c6ae02 |
in agreement with the standard result {{cite:89a40be35405b882ddf5495008b9ae25b00d9cc0}}, {{cite:6bbff6b6b8d4a595422fdc517f70bb44d3f9ea36}}, {{cite:235343349931ad80205fcf0ef8e11de257cf219f}}. The radius {{formula:192c4b4f-a044-48ca-b83b-dbd6628c2179}} (REF ) is given by
{{formula:d3ec0f54-057d-4269-9126-2ce5fcc8a3c3}}... | d | 2498de2456d67834e31493f430b25da8 |
Downstream Evaluation. We pretrain our model with Mid fusion using MEP and CPP tasks (with CANS-Similar), and employ Part weight sharing. We use either Kinetics-700 or AudioSet for fair comparisons with prior work. Table REF (a)/(b) shows short-video/audio classification results on UCF-101/ESC-50. For fair comparisons... | r | 9415a703ff5b0978d63234561c03522a |
In the previous sections, we have shown the advantages of our proposal in quantum communication applications. In this section, we demonstrate that the proposed scheme can also be adopted for quantum computing applications. In quantum computing applications, the quantum information is usually protected with the aid of n... | d | 5125fefc13ced273c492373883f8baa4 |
One primary challenge faced by multi-aperture microscope designs is data management. In this work, we utilized a single FPGA to aggregate Mobile Industry Processor Interface (MIPI) data directly from all sensors, which led to several key benefits. First, the single FPGA allowed us to directly synchronize video capture ... | d | 34c606898601b145669b9a8cc8efa9b9 |
This result has significant implications for the ground state properties of {{formula:c3d0d4a2-dddb-4b63-a8c0-e25957de1041}} . For positive {{formula:a905dc61-46d4-4a42-a336-f6f675b633c4}} , in balanced bi-partite lattices where {{formula:7ee12ec3-3354-4414-ba36-f49486ba15f4}} (examples include any hypercubic lattice)... | r | 85490aaa498616cf3e8765964ff92c2e |
We also examined the case where moiré exciton condensates with two spin species coexist.
The condensate mixture with two spin species can be described by a spinor GPE,
with the inter-species exciton-exciton interaction weaker than intra-species one {{cite:0faab0e24658c9b14ec1caa5e0c804f3a341841c}}. We numerically find ... | d | c7405f125b08dd64fd67f104ca910710 |
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