115 citations · 231 across the 17 of their papers we have counts for
17 papers
On the Identifiablility of Nonlocal Interaction Kernels in First-Order Systems of Interacting Particles on Riemannian Manifolds
Sui Tang, Malik Tuerkoen, Hanming Zhou
In this paper, we tackle a critical issue in nonparametric inference for systems of interacting particles on Riemannian manifolds: the identifiability of the interaction functions.…
Learning Transition Operators From Sparse Space-Time Samples
Christian Kümmerle, Mauro Maggioni, Sui Tang
We consider the nonlinear inverse problem of learning a transition operator from partial observations at different times, in particular from sparse observations of ent…
An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM
Yangyi Zhang, Sui Tang, Guo Yu
The Coronavirus Disease 2019 (COVID-19) has a profound impact on global health and economy, making it crucial to build accurate and interpretable data-driven predictive models for…
Higher-Order error estimates for physics-informed neural networks approximating the primitive equations
Ruimeng Hu, Quyuan Lin, Alan Raydan +1
Large-scale dynamics of the oceans and the atmosphere are governed by primitive equations (PEs). Due to the nonlinearity and nonlocality, the numerical study of the PEs is generall…
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
Mengyang Gu, Xubo Liu, Xinyi Fang +1
Marginalization of latent variables or nuisance parameters is a fundamental aspect of Bayesian inference and uncertainty quantification. In this work, we focus on scalable marginal…
Robust recovery of bandlimited graph signals via randomized dynamical sampling
Longxiu Huang, Deanna Needell, Sui Tang
Heat diffusion processes have found wide applications in modelling dynamical systems over graphs. In this paper, we consider the recovery of a -bandlimited graph signal that is…
Learning particle swarming models from data with Gaussian processes
Jinchao Feng, Charles Kulick, Yunxiang Ren +1
Interacting particle or agent systems that display a rich variety of swarming behaviours are ubiquitous in science and engineering. A fundamental and challenging goal is to underst…
Estimate the spectrum of affine dynamical systems from partial observations of a single trajectory data
Jiahui Cheng, Sui Tang
In this paper, we study the nonlinear inverse problem of estimating the spectrum of a system matrix, that drives a finite-dimensional affine dynamical system, from partial observat…
Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems
Jason Miller, Sui Tang, Ming Zhong +1
Modeling the complex interactions of systems of particles or agents is a fundamental scientific and mathematical problem that is studied in diverse fields, ranging from physics and…
Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
Fei Lu, Mauro Maggioni, Sui Tang
We consider stochastic systems of interacting particles or agents, with dynamics determined by an interaction kernel which only depends on pairwise distances. We study the problem…
On the identifiability of interaction functions in systems of interacting particles
Zhongyang Li, Fei Lu, Mauro Maggioni +2
We address a fundamental issue in the nonparametric inference for systems of interacting particles: the identifiability of the interaction functions. We prove that the interaction…
Learning interaction kernels in heterogeneous systems of agents from multiple trajectories
Fei Lu, Mauro Maggioni, Sui Tang
Systems of interacting particles or agents have wide applications in many disciplines such as Physics, Chemistry, Biology and Economics. These systems are governed by interaction l…
Nonparametric inference of interaction laws in systems of agents from trajectory data
Fei Lu, Mauro Maggioni, Sui Tang +1
Inferring the laws of interaction between particles and agents in complex dynamical systems from observational data is a fundamental challenge in a wide variety of disciplines. We…
Sensor Calibration for Off-the-Grid Spectral Estimation
Yonina C. Eldar, Wenjing Liao, Sui Tang
This paper studies sensor calibration in spectral estimation where the true frequencies are located on a continuous domain. We consider a uniform array of sensors that collects mea…
Phaseless Reconstruction from Space-Time Samples
Akram Aldroubi, llya krishtal, Sui Tang
Phaseless reconstruction from space-time samples is a nonlinear problem of recovering a function in a Hilbert space from the modulus of linear measurements $\{\lv…
Universal Spatiotemporal Sampling Sets for Discrete Spatially Invariant Evolution Systems
Sui Tang
Let be a finite abelian group and be a circular convolution operator on . The problem under consideration is how to construct minimal a…
System Identification in Dynamical Sampling
Sui Tang
We consider the problem of spatiotemporal sampling in a discrete infinite dimensional spatially invariant evolutionary process to recover an unknown convolution oper…