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Author

Pengzhan Jin

Observed name: Jin, Pengzhan
Institution: Peking University
Observed institutions: Chinese Academy of Sciences, Peking University, Brown University, National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, University of Chinese Academy of Sciences
ORCID: 0000-0002-2169-1491
Observed ORCID: 0000-0002-2169-1491
OpenAlex ID: A5009632487
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
2021 · Lu Lu, Pengzhan Jin, et al. · Nature Machine Intelligence · 4,338
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MIONet: Learning Multiple-Input Operators via Tensor Product
2022 · Pengzhan Jin, Shuai Meng, et al. · SIAM Journal on Scientific Computing · 278
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SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems
2020 · Pengzhan Jin, Zhen Zhang, et al. · Neural Networks · 234
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness
2020 · Pengzhan Jin, Lu Lu, et al. · Neural Networks · 69
Learning Poisson Systems and Trajectories of Autonomous Systems via Poisson Neural Networks
2022 · Pengzhan Jin, Zhen Zhang, et al. · IEEE Transactions on Neural Networks and Learning Systems · 61
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Tensor Neural Network and Its Numerical Integration
2023 · Yifan Wang, Hehu Xie, et al. · Journal of Computational Mathematics · 55
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Deep Hamiltonian networks based on symplectic integrators
2020 · Zhu, Aiqing, Jin, Pengzhan, et al. · arXiv (Cornell University) · 30
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On Numerical Integration in Neural Ordinary Differential Equations
2022 · Zhu, Aiqing, Jin, Pengzhan, et al. · arXiv (Cornell University) · 21
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A hybrid iterative method based on MIONet for PDEs: Theory and numerical examples
2025 · Jun Hu, Pengzhan Jin · Mathematics of Computation · 19
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Optimal unit triangular factorization of symplectic matrices
2022 · Pengzhan Jin, Zhangli Lin, et al. · Linear Algebra and its Applications · 13
Symplectic networks: Intrinsic structure-preserving networks for identifying Hamiltonian systems.
2020 · Pengzhan Jin, Aiqing Zhu, et al. · arXiv (Cornell University) · 13
Unit Triangular Factorization of the Matrix Symplectic Group
2020 · Pengzhan Jin, Yifa Tang, et al. · SIAM Journal on Matrix Analysis and Applications · 13
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Learning solution operators of PDEs defined on varying domains via MIONet
2024 · Xiao, Shanshan, Jin, Pengzhan, et al. · arXiv (Cornell University) · 10
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Approximation capabilities of measure-preserving neural networks
2021 · Aiqing Zhu, Pengzhan Jin, et al. · Neural Networks · 10
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Inverse modified differential equations for discovery of dynamics
2020 · Zhu, Aiqing, Jin, Pengzhan, et al. · arXiv (Cornell University) · 10
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Two-hidden-layer ReLU neural networks and finite elements
2026 · Pengzhan Jin · Neural Networks · 5
Manifold Function Encoder: Identifying Different Functions Defined on Different Manifolds
2025 · Hu, Jun, Jin, Pengzhan, et al. · arXiv (Cornell University) · 4
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A Deformation-Based Framework for Learning Solution Mappings of PDEs Defined on Varying Domains
2026 · Shanshan Xiao, Pengzhan Jin, et al. · SIAM Journal on Numerical Analysis · 3
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CSympNet-ID: conformal-symplectic map learning for linearly damped Hamiltonian systems
2026 · Gong, Jiale, Jin, Pengzhan, et al. · arXiv (Cornell University) · 1
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Experimental observation on a low-rank tensor model for eigenvalue problems
2023 · Hu, Jun, Jin, Pengzhan · arXiv (Cornell University) · 1
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Exact Representation of Piecewise Polynomial Finite Element Functions by Two-Hidden-Layer Multilayer Perceptrons
2026 · Hu, Jun, Jin, Pengzhan, et al. · arXiv (Cornell University)
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Learning Operators of Geometry with an Interface Autoencoder
2026 · Zhu, Aiqing, Jin, Pengzhan · arXiv (Cornell University)
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MENO: Memory-Efficient Neural Operator
2026 · Xu, Shengyang, Zhang, Weijun, et al. · arXiv (Cornell University)
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DeepONet: Learning nonlinear operators based on the universal approximation theorem of operators
2019 · Lu Lu, Pengzhan Jin, et al.
Works count: 25
Citation count: 5,862
H-index: 13
I10-index: 16
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