Bound-preserving discontinuous Galerkin methods for relativistic hydrodynamics. - Tong Qin 002; Chi-Wang Shu; Yang Yang 014 (J. Comput. Phys., 2016)

Reducing Parameter Space for Neural Network Training. - Tong Qin 002; Ling Zhou 001; Dongbin Xiu (CoRR, 2018)

Implicit Positivity-Preserving High-Order Discontinuous Galerkin Methods for Conservation Laws. - Tong Qin 002; Chi-Wang Shu (SIAM J. Sci. Comput., 2018)

A neural network approach for uncertainty quantification for time-dependent problems with random parameters. - Tong Qin 002; Zhen Chen; John D. Jakeman; Dongbin Xiu (CoRR, 2019)

Data driven governing equations approximation using deep neural networks. - Tong Qin 002; Kailiang Wu; Dongbin Xiu (J. Comput. Phys., 2019)

A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data. - Jun Hou; Tong Qin 002; Kailiang Wu; Dongbin Xiu (CoRR, 2020)

Data-driven learning of non-autonomous systems. - Tong Qin 002; Zhen Chen; John D. Jakeman; Dongbin Xiu (CoRR, 2020)

Structure-Preserving Method for Reconstructing Unknown Hamiltonian Systems From Trajectory Data. - Kailiang Wu; Tong Qin 002; Dongbin Xiu (SIAM J. Sci. Comput., 2020)

Data-Driven Learning of Nonautonomous Systems. - Tong Qin 002; Zhen Chen; John D. Jakeman; Dongbin Xiu (SIAM J. Sci. Comput., 2021)