孙昊｜中国海洋大学｜学者主页

2026

Data-driven discovery of governing differential equations across physical systems

Siyu Lou, Hao Xu, Wenguan Wang, Lu Lu, Hao Sun, Yang Liu, Linfeng Zhang, Dongxiao Zhang, Yuntian Chen

arXiv preprint

2026

Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

Shizheng Wen, Mingyuan Chi, Tianwei Yu, Ben Moseley, Mike Yan Michelis, Pu Ren, Hao Sun, Siddhartha Mishra

arXiv preprint

2026

Physical-Field Reconstruction from Sparse Observations: When Are Diffusion Models Preferable to Deterministic Regression?

Hao Zhou, Rui Zhang, Qi Wang, Hao Sun

arXiv preprint

2026

Large language models for partial differential equation workflows

Han Wan, Rui Zhang, Hao Sun

arXiv preprint

2026

Physics Transformer: Tailoring Transformer for General PDE Prediction

Guoze Sun, Rui Zhang, Jiankai Tang, Mengtao Yan, Runze Mao, Zhi X. Chen, Hao Sun

arXiv preprint

2026

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion

Guoze Sun, Tianya Miao, Haoyang Huang, Huaguan Chen, Han Wan, Rui Zhang, Hao Sun

arXiv preprint

2026

PerFlow: Physics-Embedded Rectified Flow for Efficient Reconstruction and Uncertainty Quantification of Spatiotemporal Dynamics

Hao Zhou, Rui Zhang, Han Wan, Hao Sun

arXiv preprint

2026

NPSolver: Neural Poisson Solver with Iterative Physics Supervision

Bocheng Zeng, Rui Zhang, Runze Mao, Mengtao Yan, Xuan Bai, Yang Liu, Zhi X. Chen, Hao Sun

arXiv preprint

2025

Spectral-inspired Operator Learning with Limited Data and Unknown Physics

Han Wan, Rui Zhang, Hao Sun

arXiv preprint

DOI

2025

PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems

Han Wan, Rui Zhang, Qi Wang, Yang Liu, Hao Sun

arXiv preprint

2025

PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Burst-Sampled Spatiotemporal Dynamics

Han Wan, Qi Wang, Yuan Mi, Rui Zhang, Hao Sun

arXiv preprint

2025

Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows

Mengtao Yan, Qi Wang, Haining Wang, Ruizhi Chengze, Yi Zhang, Hongsheng Liu, Zidong Wang, Fan Yu, Qi Qi, Hao Sun

arXiv preprint

DOI

2025

Stable spectral neural operator for learning stiff PDE systems from limited data

Rui Zhang, Han Wan, Yang Liu, Hao Sun

arXiv preprint

2025

Benchmarking neural surrogates on realistic spatiotemporal multiphysics flows

Runze Mao, Rui Zhang, Xuan Bai, Tianhao Wu, Teng Zhang, Zhenyi Chen, Minqi Lin, Bocheng Zeng, Yangchen Xu, Yingxuan Xiang, Haoze Zhang, Shubham Goswami, Pierre A. Dawe, Yifan Xu, Zhenhua An, Mengtao Yan, Xiaoyi Lu, Yi Wang, Rongbo Bai, Haobu Gao, Xiaohang Fang, Han Li, Hao Sun, Zhi X. Chen

arXiv preprint

2025

SlotPi: Physics-informed Object-centric Reasoning Models

Jian Li, Wan Han, Ning Lin, Yu-Liang Zhan, Ruizhi Chengze, Haining Wang, Yi Zhang, Hongsheng Liu, Zidong Wang, Fan Yu, Hao Sun

arXiv preprint

DOI

2025

Differentiable Sparse Identification of Lagrangian Dynamics

Zitong Zhang, Hao Sun

arXiv preprint

2025

MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation

Qi Wang, Yuan Mi, Haoyun Wang, Yi Zhang, Ruizhi Chengze, Hongsheng Liu, Ji-Rong Wen, Hao Sun

arXiv preprint

2025

OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics

Rui Zhang, Qi Meng, Han Wan, Yang Liu, Zhi-Ming Ma, Hao Sun

arXiv preprint

2025

PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows

Huaguan Chen, Yang Liu, Hao Sun

arXiv preprint

2025

Hierarchical Physics-Embedded Learning for Partially Known Spatiotemporal Dynamics

Xizhe Wang, Xiaobin Song, Hongbo Zhao, Qingshan Jia, Qianchuan Zhao, Hao Sun, Benben Jiang

arXiv preprint

2024

P$^2$C$^2$Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics

Qi Wang, Pu Ren, Hao Zhou, Xin-Yang Liu, Zhiwen Deng, Yi Zhang, Ruizhi Chengze, Hongsheng Liu, Zidong Wang, Jian-Xun Wang, Ji-Rong_Wen, Hao Sun, Yang Liu

arXiv preprint

2024

Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction

Yuan Mi, Pu Ren, Hongteng Xu, Hongsheng Liu, Zidong Wang, Yike Guo, Ji-Rong Wen, Hao Sun, Yang Liu

arXiv preprint

2024

PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems

Bocheng Zeng, Qi Wang, Mengtao Yan, Yang Liu, Ruizhi Chengze, Yi Zhang, Hongsheng Liu, Zidong Wang, Hao Sun

arXiv preprint

2024

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures

R. Bailey Bond, Pu Ren, Jerome F. Hajjar, Hao Sun

arXiv preprint

2024

Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target

Zitong Zhang, Yang Liu, Hao Sun

arXiv preprint

2023

Physics-informed neural network for seismic wave inversion in layered semi-infinite domain

Pu Ren, Chengping Rao, Hao Sun, Yang Liu

arXiv preprint

2023

RSRM: Reinforcement Symbolic Regression Machine

Yilong Xu, Yang Liu, Hao Sun

arXiv preprint

2022

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

Xin-Yang Liu, Min Zhu, Lu Lu, Hao Sun, Jian-Xun Wang

arXiv preprint

DOI

2022

An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection

R. Bailey Bond, Pu Ren, Jerome F. Hajjar, Hao Sun

arXiv preprint

DOI

2022

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

Luning Sun, Daniel Zhengyu Huang, Hao Sun, Jian-Xun Wang

arXiv preprint

2022

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

arXiv preprint

2022

Distilling Governing Laws and Source Input for Dynamical Systems from Videos

Lele Luan, Yang Liu, Hao Sun

arXiv preprint

2022

Physics-informed Deep Super-resolution for Spatiotemporal Data

Pu Ren, Chengping Rao, Yang Liu, Zihan Ma, Qi Wang, Jian-Xun Wang, Hao Sun

arXiv preprint

2022

Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning

Chengping Rao, Pu Ren, Yang Liu, Hao Sun

arXiv preprint

2022

SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain

Pu Ren, Chengping Rao, Su Chen, Jian-Xun Wang, Hao Sun, Yang Liu

arXiv preprint

2021

PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs

Pu Ren, Chengping Rao, Yang Liu, Jianxun Wang, Hao Sun

arXiv preprint

DOI

2021

Hard Encoding of Physics for Learning Spatiotemporal Dynamics

Chengping Rao, Hao Sun, Yang Liu

arXiv preprint

2021

Physics-informed Spline Learning for Nonlinear Dynamics Discovery

Fangzheng Sun, Yang Liu, Hao Sun

arXiv preprint

2021

Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos

Lele Luan, Yang Liu, Hao Sun

arXiv preprint

2021

Encoding physics to learn reaction-diffusion processes

Chengping Rao, Pu Ren, Qi Wang, Oral Buyukozturk, Hao Sun, Yang Liu

arXiv preprint

2020

Physics-Informed Multi-LSTM Networks for Metamodeling of Nonlinear Structures

Ruiyang Zhang, Yang Liu, Hao Sun

arXiv preprint

DOI

2020

Physics informed deep learning for computational elastodynamics without labeled data

Chengping Rao, Hao Sun, Yang Liu

arXiv preprint

2020

Physics-informed learning of governing equations from scarce data

Zhao Chen, Yang Liu, Hao Sun

arXiv preprint

DOI

2020

Extracting full-field subpixel structural displacements from videos via deep learning

Lele Luan, Jingwei Zheng, Yongchao Yang, Ming L. Wang, Hao Sun

arXiv preprint

DOI

2020

Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting

Pu Ren, Xinyu Chen, Lijun Sun, Hao Sun

arXiv preprint

2020

Sparse representation for damage identification of structural systems

Zhao Chen, Hao Sun

arXiv preprint

2019

Physics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling

Ruiyang Zhang, Yang Liu, Hao Sun

arXiv preprint

精选作品

期刊论文

Physics-informed deep learning for incompressible laminar flows

预印本

Data-driven discovery of governing differential equations across physical systems

Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

Physical-Field Reconstruction from Sparse Observations: When Are Diffusion Models Preferable to Deterministic Regression?

Large language models for partial differential equation workflows

Physics Transformer: Tailoring Transformer for General PDE Prediction

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion

PerFlow: Physics-Embedded Rectified Flow for Efficient Reconstruction and Uncertainty Quantification of Spatiotemporal Dynamics

NPSolver: Neural Poisson Solver with Iterative Physics Supervision

Spectral-inspired Operator Learning with Limited Data and Unknown Physics

PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems

PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Burst-Sampled Spatiotemporal Dynamics

Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows

Stable spectral neural operator for learning stiff PDE systems from limited data

Benchmarking neural surrogates on realistic spatiotemporal multiphysics flows

SlotPi: Physics-informed Object-centric Reasoning Models

Differentiable Sparse Identification of Lagrangian Dynamics

MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation

OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics

PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows

Hierarchical Physics-Embedded Learning for Partially Known Spatiotemporal Dynamics

P$^2$C$^2$Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics

Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction

PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures

Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target

Physics-informed neural network for seismic wave inversion in layered semi-infinite domain

RSRM: Reinforcement Symbolic Regression Machine

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

Distilling Governing Laws and Source Input for Dynamical Systems from Videos

Physics-informed Deep Super-resolution for Spatiotemporal Data

Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning

SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain

PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs

Hard Encoding of Physics for Learning Spatiotemporal Dynamics

Physics-informed Spline Learning for Nonlinear Dynamics Discovery

Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos

Encoding physics to learn reaction-diffusion processes

Physics-Informed Multi-LSTM Networks for Metamodeling of Nonlinear Structures

Physics informed deep learning for computational elastodynamics without labeled data

Physics-informed learning of governing equations from scarce data

Extracting full-field subpixel structural displacements from videos via deep learning

Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting

Sparse representation for damage identification of structural systems

Physics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling

研究方向