197 citations · 401 across the 4 of their papers we have counts for
5 papers
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…
Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov Arnold Networks
Yizheng Wang, Jia Sun, Jinshuai Bai +5
AI for partial differential equations (PDEs) has garnered significant attention, particularly with the emergence of Physics-informed neural networks (PINNs). The recent advent of K…
DCEM: A deep complementary energy method for solid mechanics
Yizheng Wang, Jia Sun, Timon Rabczuk +1
In recent years, the rapid advancement of deep learning has significantly impacted various fields, particularly in solving partial differential equations (PDEs) in the realm of sol…
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations
Jia Sun, Yinghua Liu, Yizheng Wang +2
We proposed the boundary-integral type neural networks (BINN) for the boundary value problems in computational mechanics. The boundary integral equations are employed to transfer a…
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
Yizheng Wang, Jia Sun, Wei Li +2
We propose a conservative energy method based on neural networks with subdomains for solving variational problems (CENN), where the admissible function satisfying the essential bou…