64 citations · 79 across the 6 of their papers we have counts for
6 papers
PCNet: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics
Qi Wang, Pu Ren, Hao Zhou +10
When solving partial differential equations (PDEs), classical numerical methods often require fine mesh grids and small time stepping to meet stability, consistency, and convergenc…
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems
Bocheng Zeng, Qi Wang, Mengtao Yan +6
Solving partial differential equations (PDEs) serves as a cornerstone for modeling complex dynamical systems. Recent progresses have demonstrated grand benefits of data-driven neur…
Discovering physical laws with parallel symbolic enumeration
Kai Ruan, Yilong Xu, Ze-Feng Gao +4
Symbolic regression plays a crucial role in modern scientific research thanks to its capability of discovering concise and interpretable mathematical expressions from data. A key c…
Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target
Zitong Zhang, Yang Liu, Hao Sun
Data-driven discovery of governing equations has kindled significant interests in many science and engineering areas. Existing studies primarily focus on uncovering equations that…
AI-accelerated Discovery of Altermagnetic Materials
Ze-Feng Gao, Shuai Qu, Bocheng Zeng +5
Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism. Although altermagnets h…
Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search
Fangzheng Sun, Yang Liu, Jian-Xun Wang +1
Nonlinear dynamics is ubiquitous in nature and commonly seen in various science and engineering disciplines. Distilling analytical expressions that govern nonlinear dynamics from l…