Search Results for author: Wensheng Li

Found 2 papers, 1 papers with code

Understanding Deep Neural Networks via Linear Separability of Hidden Layers

no code implementations26 Jul 2023 Chao Zhang, Xinyu Chen, Wensheng Li, Lixue Liu, Wei Wu, DaCheng Tao

In this paper, we measure the linear separability of hidden layer outputs to study the characteristics of deep neural networks.

Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method

1 code implementation18 May 2022 Wensheng Li, Chao Zhang, Chuncheng Wang, Hanting Guan, DaCheng Tao

Physics-informed neural networks (PINNs) provide a deep learning framework for numerically solving partial differential equations (PDEs), and have been widely used in a variety of PDE problems.

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