15 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.LG2026★ 15 cited
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions
Shijun Zhang, Jianfeng Lu, Hongkai Zhao
This paper explores the expressive power of deep neural networks for a diverse range of activation functions. An activation function set is defined to encompass the m…
stat.ML2026
Sobolev Approximation by Fixed-Size Neural Networks with Arbitrary Accuracy
Baicheng Li, Haizhao Yang, Shijun Zhang
In this work, we investigate new activation functions for achieving arbitrary-accuracy Sobolev approximation by fixed-size neural networks. We first show that any function in $W^{2…
cs.LG2026
Multigrade Neural Network Approximation
Shijun Zhang, Zuowei Shen, Yuesheng Xu
We study multigrade deep learning (MGDL) as a principled framework for structured error refinement in deep neural networks. While the approximation power of neural networks is now…