Search Results for author: Junjun Yan

Found 4 papers, 2 papers with code

Proposing an intelligent mesh smoothing method with graph neural networks

no code implementations24 Sep 2023 Zhichao Wang, Xinhai Chen, Junjun Yan, Jie Liu

With a lightweight model, GMSNet can effectively smoothing mesh nodes with varying degrees and remain unaffected by the order of input data.

Data Augmentation

Auxiliary-Tasks Learning for Physics-Informed Neural Network-Based Partial Differential Equations Solving

1 code implementation12 Jul 2023 Junjun Yan, Xinhai Chen, Zhichao Wang, Enqiang Zhou, Jie Liu

To alleviate these issues, we proposed auxiliary-task learning-based physics-informed neural networks (ATL-PINNs), which provide four different auxiliary-task learning modes and investigate their performance compared with original PINNs.

ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations

1 code implementation15 Jun 2023 Junjun Yan, Xinhai Chen, Zhichao Wang, Enqiang Zhoui, Jie Liu

To address the issue of low accuracy and convergence problems of existing PINNs, we propose a self-training physics-informed neural network, ST-PINN.

Pseudo Label Self-Learning

An Improved Structured Mesh Generation Method Based on Physics-informed Neural Networks

no code implementations18 Oct 2022 Xinhai Chen, Jie Liu, Junjun Yan, Zhichao Wang, Chunye Gong

To improve the prediction accuracy of the neural network, we also introduce a novel auxiliary line strategy and an efficient network model during meshing.

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