The Impact of Geometric Complexity on Neural Collapse in Transfer Learning

24 May 2024

Papers citing "The Impact of Geometric Complexity on Neural Collapse in Transfer Learning"

8 / 8 papers shown

Title
Leveraging free energy in pretraining model selection for improved fine-tuning Michael Munn Susan Wei 19 0 0 08 Oct 2024
Sparse Modular Activation for Efficient Sequence Modeling Liliang Ren Yang Liu Shuohang Wang Yichong Xu Chenguang Zhu Chengxiang Zhai 43 13 0 19 Jun 2023
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 53 30 0 27 Sep 2022
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 81 72 0 29 Sep 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 264 1,798 0 14 Dec 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 2016
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