13 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Adaptively Point-weighting Curriculum Learning
Wensheng Li, Yichao Tian, Hao Wang +4
Curriculum learning (CL) mimics human learning, in which easy samples are learned first, followed by harder samples, and has become an effective method for training deep networks.…
cs.LG2023★ 1 cited
Understanding Deep Neural Networks via Linear Separability of Hidden Layers
Chao Zhang, Xinyu Chen, Wensheng Li +3
In this paper, we measure the linear separability of hidden layer outputs to study the characteristics of deep neural networks. In particular, we first propose Minkowski difference…
cs.LG2022★ 13 cited
Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method
Wensheng Li, Chao Zhang, Chuncheng Wang +2
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…