Követés
Sui Tang
Cím
Hivatkozott rá
Hivatkozott rá
Év
Dynamical sampling
A Aldroubi, C Cabrelli, U Molter, S Tang
Applied and Computational Harmonic Analysis 42 (3), 378-401, 2017
1322017
Nonparametric inference of interaction laws in systems of agents from trajectory data
F Lu, M Zhong, S Tang, M Maggioni
Proceedings of the National Academy of Sciences 116 (29), 14424-14433, 2019
1162019
Learning interaction kernels in heterogeneous systems of agents from multiple trajectories
F Lu, M Maggioni, S Tang
Journal of Machine Learning Research 22 (32), 1-67, 2021
642021
On the identifiability of interaction functions in systems of interacting particles
Z Li, F Lu, M Maggioni, S Tang, C Zhang
Stochastic Processes and their Applications 132, 135-163, 2021
342021
System identification in dynamical sampling
S Tang
Advances in Computational Mathematics 43, 555-580, 2017
242017
Dynamical sampling in hybrid shift invariant spaces
R Aceska, S Tang, V Furst
Operator Methods in Wavelets, Tilings, and Frames 626, 149, 2014
232014
Sensor calibration for off-the-grid spectral estimation
YC Eldar, W Liao, S Tang
Applied and Computational Harmonic Analysis 48 (2), 570-598, 2020
222020
Learning theory for inferring interaction kernels in second-order interacting agent systems
J Miller, S Tang, M Zhong, M Maggioni
Sampling Theory, Signal Processing, and Data Analysis 21 (1), 21, 2023
192023
Multidimensional signal recovery in discrete evolution systems via spatiotemporal trade off
R Aceska, A Petrosyan, S Tang
Sampling Theory in Signal and Image Processing 14, 153-169, 2015
152015
Phaseless reconstruction from space–time samples
A Aldroubi, I Krishtal, S Tang
Applied and Computational Harmonic Analysis 48 (1), 395-414, 2020
132020
Learning particle swarming models from data with Gaussian processes
J Feng, C Kulick, Y Ren, S Tang
Mathematics of Computation 93 (349), 2391-2437, 2024
11*2024
Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
F Lu, M Maggioni, S Tang
Foundations of Computational Mathematics, 1013–1067, 2021
112021
Higher-order error estimates for physics-informed neural networks approximating the primitive equations
R Hu, Q Lin, A Raydan, S Tang
Partial Differential Equations and Applications 4 (4), 34, 2023
102023
An interpretable hybrid predictive model of COVID-19 cases using autoregressive model and LSTM
Y Zhang, S Tang, G Yu
Scientific reports 13 (1), 6708, 2023
92023
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
M Gu, X Liu, X Fang, S Tang
arXiv preprint arXiv:2203.08389, 2022
62022
Estimate the spectrum of affine dynamical systems from partial observations of a single trajectory data
J Cheng, S Tang
Inverse Problems 38 (1), 015004, 2021
62021
Universal spatiotemporal sampling sets for discrete spatially invariant evolution processes
S Tang
IEEE Transactions on Information Theory 63 (9), 5518-5528, 2017
62017
Robust estimation of smooth graph signals from randomized space–time samples
L Huang, D Needell, S Tang
Information and Inference: A Journal of the IMA 13 (2), iaae012, 2024
5*2024
Phase retrieval of evolving signals from space-time samples
A Aldroubi, I Krishtal, S Tang
2017 International Conference on Sampling Theory and Applications (SampTA …, 2017
52017
Dynamical sampling of two-dimensional temporally-varying signals
R Aceska, A Petrosyan, S Tang
2015 International Conference on Sampling Theory and Applications (SampTA …, 2015
32015
A rendszer jelenleg nem tudja elvégezni a műveletet. Próbálkozzon újra később.
Cikkek 1–20