Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. - Sheng Liu; Xiao Li 026; Yuexiang Zhai; Chong You; Zhihui Zhu; Carlos Fernandez-Granda; Qing Qu 001 (NeurIPS, 2021)

A Geometric Analysis of Neural Collapse with Unconstrained Features. - Zhihui Zhu; Tianyu Ding; Jinxin Zhou; Xiao Li 026; Chong You; Jeremias Sulam; Qing Qu 001 (NeurIPS, 2021)

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. - Jinxin Zhou; Xiao Li 026; Tianyu Ding; Chong You; Qing Qu 001; Zhihui Zhu (ICML, 2022)

Are All Losses Created Equal: A Neural Collapse Perspective. - Jinxin Zhou; Chong You; Xiao Li 026; Kangning Liu; Sheng Liu; Qing Qu 001; Zhihui Zhu (NeurIPS, 2022)

Principled and Efficient Transfer Learning of Deep Models via Neural Collapse. - Xiao Li 026; Sheng Liu; Jinxin Zhou; Xinyu Lu; Carlos Fernandez-Granda; Zhihui Zhu; Qing Qu 001 (CoRR, 2022)

Understanding and Improving Transfer Learning of Deep Models via Neural Collapse. - Xiao Li 026; Sheng Liu; Jinxin Zhou; Xinyu Lu; Carlos Fernandez-Granda; Zhihui Zhu; Qing Qu 001 (Trans. Mach. Learn. Res., 2024)