613 citations · 1k across the 21 of their papers we have counts for
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physics.geo-ph2022★ 5 cited
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain
Pu Ren, Chengping Rao, Su Chen +3
There has been an increasing interest in integrating physics knowledge and machine learning for modeling dynamical systems. However, very limited studies have been conducted on sei…
cs.AI2022★ 14 cited
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…
cs.LG2022★ 12 cited
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao, Pu Ren, Yang Liu +1
There have been growing interests in leveraging experimental measurements to discover the underlying partial differential equations (PDEs) that govern complex physical phenomena. A…