2 papers
cs.LG2025
High-fidelity Multiphysics Modelling for Rapid Predictions Using Physics-informed Parallel Neural Operator
Biao Yuan, He Wang, Yanjie Song +2
Modelling complex multiphysics systems governed by nonlinear and strongly coupled partial differential equations (PDEs) is a cornerstone in computational science and engineering. H…
cs.LG2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
Biao Yuan, Ana Heitor, He Wang +1
The emergence of neural networks constrained by physical governing equations has sparked a new trend in deep learning research, which is known as Physics-Informed Neural Networks (…