92 citations · 92 across the 3 of their papers we have counts for
4 papers
Discrete Solution Operator Learning for Geometry-Dependent PDEs
Jinshuai Bai, Haolin Li, Zahra Sharif Khodaei +3
Neural operator learning accelerates PDE solution by approximating operators as mappings between continuous function spaces. Yet in many engineering settings, varying geometry indu…
Energy-based physics-informed neural network for frictionless contact problems under large deformation
Jinshuai Bai, Zhongya Lin, Yizheng Wang +5
Numerical methods for contact mechanics are of great importance in engineering applications, enabling the prediction and analysis of complex surface interactions under various cond…
Artificial intelligence for partial differential equations in computational mechanics: A review
Yizheng Wang, Jinshuai Bai, Zhongya Lin +9
In recent years, Artificial intelligence (AI) has become ubiquitous, empowering various fields, especially integrating artificial intelligence and traditional science (AI for Scien…
Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear PDEs
Jinshuai Bai, Gui-Rong Liu, Ashish Gupta +3
Our recent intensive study has found that physics-informed neural networks (PINN) tend to be local approximators after training. This observation leads to this novel physics-inform…