Neural Collapse: A Review on Modelling Principles and Generalization

8 June 2022

Papers citing "Neural Collapse: A Review on Modelling Principles and Generalization"

12 / 12 papers shown

Title
Formation of Representations in Neural Networks Liu Ziyin Isaac Chuang Tomer Galanti T. Poggio 34 4 0 03 Oct 2024
Geometric Analysis of Unconstrained Feature Models with $d=K$ Yi Shen Shao Gu 21 0 0 15 Jul 2024
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection Yingwen Wu Ruiji Yu Xinwen Cheng Zhengbao He Xiaolin Huang OODD 60 1 0 28 May 2024
Spectral regularization for adversarially-robust representation learning Sheng Yang Jacob A. Zavatone-Veth C. Pehlevan AAML OOD 30 0 0 27 May 2024
Pushing Boundaries: Mixup's Influence on Neural Collapse Quinn Fisher Haoming Meng V. Papyan AAML UQCV 28 5 0 09 Feb 2024
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks Vignesh Kothapalli Tom Tirer Joan Bruna 19 10 0 04 Jul 2023
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse Xiao Li Sheng Liu Jin-li Zhou Xin Lu C. Fernandez‐Granda Zhihui Zhu Q. Qu AAML 16 18 0 23 Dec 2022
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning Shuo Xie Jiahao Qiu Ankita Pasad Li Du Qing Qu Hongyuan Mei 17 16 0 18 Oct 2022
Nearest Class-Center Simplification through Intermediate Layers Ido Ben-Shaul S. Dekel 29 26 0 21 Jan 2022
An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji Yiping Lu Yiliang Zhang Zhun Deng Weijie J. Su 114 65 0 06 Oct 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 114 162 0 29 Jan 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,202 0 24 Nov 2016