Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural
Networks

Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks

21 May 2024

Xin-Chun Li

Papers citing "Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks"

7 / 7 papers shown

Title
Plateau in Monotonic Linear Interpolation -- A "Biased" View of Loss Landscape for Deep Networks Xiang Wang Annie Wang Mo Zhou Rong Ge MoMe 158 10 0 03 Oct 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 239 312 0 11 Sep 2022
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes James Lucas Juhan Bae Michael Ruogu Zhang Stanislav Fort R. Zemel Roger C. Grosse MoMe 146 28 0 22 Apr 2021
Optimizing Mode Connectivity via Neuron Alignment N. Joseph Tatro Pin-Yu Chen Payel Das Igor Melnyk P. Sattigeri Rongjie Lai MoMe 223 80 0 05 Sep 2020
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,196 0 16 Nov 2016
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 1,184 0 30 Nov 2014