1 citations · 1 across the 1 of their papers we have counts for
4 papers
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems
Sijing Li, Cheng Zhang, Zhiwen Zhang +1
In this paper, we consider a Bayesian inverse problem modeled by elliptic partial differential equations (PDEs). Specifically, we propose a data-driven and model-based approach to…
Efficient multiscale methods for the semiclassical Schrödinger equation with time-dependent potentials
Jingrun Chen, Sijing Li, Zhiwen Zhang
The semiclassical Schrödinger equation with time-dependent potentials is an important model to study electron dynamics under external controls in the mean-field picture. In this pa…
Solving high-dimensional nonlinear filtering problems using a tensor train decomposition method
Sijing Li, Zhongjian Wang, Stephen S. T. Yau +1
In this paper, we propose an efficient numerical method to solve high-dimensional nonlinear filtering (NLF) problems. Specifically, we use the tensor train decomposition method to…
A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction
Sijing Li, Zhiwen Zhang, Hongkai Zhao
We propose a data-driven approach to solve multiscale elliptic PDEs with random coefficients based on the intrinsic low dimension structure of the underlying elliptic differential…