54 citations · 61 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2024★ 5 cited
Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects
Weiwei Zhang, Wei Suo, Jiahao Song +1
In recent years, Physics-Informed Neural Networks (PINNs) have become a representative method for solving partial differential equations (PDEs) with neural networks. PINNs provide…
physics.flu-dyn2024★ 54 cited
A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation
Wenbo Cao, Jiahao Song, Weiwei Zhang
Physics-informed neural networks (PINNs) have recently become a new popular method for solving forward and inverse problems governed by partial differential equations (PDEs). Howev…
cs.CE2024★ 2 cited
VW-PINNs: A volume weighting method for PDE residuals in physics-informed neural networks
Jiahao Song, Wenbo Cao, Fei Liao +1
Physics-informed neural networks (PINNs) have shown remarkable prospects in the solving the forward and inverse problems involving partial differential equations (PDEs). The method…