Pengzhan Jin

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Differential Equations

Top Venues

Neural Networks

SIAM J. Matrix Anal. Appl.

IEEE Trans. Neural Networks Learn. Syst.

Publications

Jun Hu, Pengzhan Jin
A hybrid iterative method based on MIONet for PDEs: Theory and numerical examples. CoRR (2024)
Shanshan Xiao, Pengzhan Jin, Yifa Tang
Learning solution operators of PDEs defined on varying domains via MIONet. CoRR (2024)
Pengzhan Jin
Shallow ReLU neural networks and finite elements. CoRR (2024)
Jun Hu, Pengzhan Jin
Experimental observation on a low-rank tensor model for eigenvalue problems. CoRR (2023)
Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis
Learning Poisson Systems and Trajectories of Autonomous Systems via Poisson Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
Pengzhan Jin, Shuai Meng, Lu Lu
MIONet: Learning multiple-input operators via tensor product. CoRR (2022)
Pengzhan Jin, Shuai Meng, Lu Lu
MIONet: Learning Multiple-Input Operators via Tensor Product. SIAM J. Sci. Comput. 44 (6) (2022)
Aiqing Zhu, Pengzhan Jin, Yifa Tang
Approximation capabilities of measure-preserving neural networks. Neural Networks 147 (2022)
Aiqing Zhu, Pengzhan Jin, Beibei Zhu, Yifa Tang
On Numerical Integration in Neural Ordinary Differential Equations. ICML (2022)
Yifan Wang, Pengzhan Jin, Hehu Xie
Tensor Neural Network and Its Numerical Integration. CoRR (2022)
Aiqing Zhu, Pengzhan Jin, Beibei Zhu, Yifa Tang
On Numerical Integration in Neural Ordinary Differential Equations. CoRR (2022)
Lu Lu, Pengzhan Jin, Guofei Pang, Zhongqiang Zhang, George Em Karniadakis
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators. Nat. Mach. Intell. 3 (3) (2021)
Aiqing Zhu, Pengzhan Jin, Yifa Tang
Approximation capabilities of measure-preserving neural networks. CoRR (2021)
Aiqing Zhu, Pengzhan Jin, Yifa Tang
Deep Hamiltonian networks based on symplectic integrators. CoRR (2020)
Aiqing Zhu, Pengzhan Jin, Yifa Tang
Inverse modified differential equations for discovery of dynamics. CoRR (2020)
Pengzhan Jin, Yifa Tang, Aiqing Zhu
Unit Triangular Factorization of the Matrix Symplectic Group. SIAM J. Matrix Anal. Appl. 41 (4) (2020)
Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks. CoRR (2020)
Pengzhan Jin, Zhen Zhang, Aiqing Zhu, Yifa Tang, George Em Karniadakis
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems. Neural Networks 132 (2020)
Pengzhan Jin, Aiqing Zhu, George Em Karniadakis, Yifa Tang
Symplectic networks: Intrinsic structure-preserving networks for identifying Hamiltonian systems. CoRR (2020)
Pengzhan Jin, Lu Lu, Yifa Tang, George Em Karniadakis
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness. Neural Networks 130 (2020)
Lu Lu, Pengzhan Jin, George Em Karniadakis
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators. CoRR (2019)
Pengzhan Jin, Lu Lu, Yifa Tang, George E. Karniadakis
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness. CoRR (2019)