A Generalized Prony Method for Filter Recovery in Evolutionary System via Spatiotemporal Trade Off. - Sui Tang (CoRR, 2015)

System identification in dynamical sampling. - Sui Tang (Adv. Comput. Math., 2017)

Phaseless Reconstruction from Space-Time Samples. - Akram Aldroubi; Ilya A. Krishtal; Sui Tang (CoRR, 2017)

Sensor Calibration for Off-the-Grid Spectral Estimation. - Yonina C. Eldar; Wenjing Liao; Sui Tang (CoRR, 2017)

Universal Spatiotemporal Sampling Sets for Discrete Spatially Invariant Evolution Systems. - Sui Tang (CoRR, 2017)

Universal Spatiotemporal Sampling Sets for Discrete Spatially Invariant Evolution Processes. - Sui Tang (IEEE Trans. Inf. Theory, 2017)

Nonparametric inference of interaction laws in systems of agents from trajectory data. - Fei Lu 016; Mauro Maggioni; Sui Tang; Ming Zhong 008 (CoRR, 2018)

Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems. - Jason Miller; Sui Tang; Ming Zhong 008; Mauro Maggioni (CoRR, 2020)

Estimate the spectrum of affine dynamical systems from partial observations of a single trajectory data. - Jiahui Cheng; Sui Tang (CoRR, 2021)

Data-driven discovery of interacting particle systems using Gaussian processes. - Jinchao Feng; Yunxiang Ren; Sui Tang (CoRR, 2021)

Robust recovery of bandlimited graph signals via randomized dynamical sampling. - Longxiu Huang; Deanna Needell; Sui Tang (CoRR, 2021)

Learning interaction kernels in heterogeneous systems of agents from multiple trajectories. - Fei Lu 016; Mauro Maggioni; Sui Tang (J. Mach. Learn. Res., 2021)

Higher-Order Error estimates for physics-informed neural networks approximating the primitive equations. - Ruimeng Hu; Quyuan Lin; Alan Raydan; Sui Tang (CoRR, 2022)

An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM. - Yangyi Zhang; Sui Tang; Guo Yu (CoRR, 2022)

Learning Interaction Kernels in Stochastic Systems of Interacting Particles from Multiple Trajectories. - Fei Lu 016; Mauro Maggioni; Sui Tang (Found. Comput. Math., 2022)

Space-Time Variable Density Samplings for Sparse Bandlimited Graph Signals Driven by Diffusion Operators. - Qing Yao; Longxiu Huang; Sui Tang (ICASSP, 2023)

On the Identifiablility of Nonlocal Interaction Kernels in First-Order Systems of Interacting Particles on Riemannian Manifolds. - Sui Tang; Malik Tuerkoen; Hanming Zhou (CoRR, 2023)

Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures. - Jinchao Feng; Charles Kulick; Sui Tang (CoRR, 2023)

Learning particle swarming models from data with Gaussian processes. - Jinchao Feng; Charles Kulick; Yunxiang Ren; Sui Tang (Math. Comput., 2023)

Convolutional dynamical sampling and some new results. - Longxiu Huang; A. Martina Neuman; Sui Tang; Yuying Xie (CoRR, 2024)

Random space-time sampling and reconstruction of sparse bandlimited graph diffusion field. - Longxiu Huang; Dongyang Li; Sui Tang; Qing Yao (CoRR, 2024)

On the Identifiability of Nonlocal Interaction Kernels in First-Order Systems of Interacting Particles on Riemannian Manifolds. - Sui Tang; Malik Tuerkoen; Hanming Zhou (SIAM J. Appl. Math., 2024)

Learning Transition Operators From Sparse Space-Time Samples. - Christian Kümmerle; Mauro Maggioni; Sui Tang (IEEE Trans. Inf. Theory, 2024)

A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model. - Jinchao Feng; Sui Tang (CoRR, 2025)