Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model

9 April 2024

Papers citing "Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model"

5 / 5 papers shown

Title
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection Yingwen Wu Ruiji Yu Xinwen Cheng Zhengbao He Xiaolin Huang OODD 62 1 0 28 May 2024
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data Hien Dang Tho Tran T. Nguyen Hung The Tran Nhat Ho Hung Tran 32 27 0 01 Jan 2023
An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji Yiping Lu Yiliang Zhang Zhun Deng Weijie J. Su 122 83 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 117 162 0 29 Jan 2021
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 175 1,182 0 30 Nov 2014