2 citations · 4 across the 14 of their papers we have counts for
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cs.CV2023
Proposing an intelligent mesh smoothing method with graph neural networks
Zhichao Wang, Xinhai Chen, Junjun Yan +1
In CFD, mesh smoothing methods are commonly utilized to refine the mesh quality to achieve high-precision numerical simulations. Specifically, optimization-based smoothing is used…
cs.LG2023★ 1 cited
Auxiliary-Tasks Learning for Physics-Informed Neural Network-Based Partial Differential Equations Solving
Junjun Yan, Xinhai Chen, Zhichao Wang +2
Physics-informed neural networks (PINNs) have emerged as promising surrogate modes for solving partial differential equations (PDEs). Their effectiveness lies in the ability to cap…
cs.LG2023★ 2 cited
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
Junjun Yan, Xinhai Chen, Zhichao Wang +2
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs),…