Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2210.01019
Cited By
v1
v2 (latest)
Plateau in Monotonic Linear Interpolation -- A "Biased" View of Loss Landscape for Deep Networks
International Conference on Learning Representations (ICLR), 2022
3 October 2022
Xiang Wang
Annie Wang
Mo Zhou
Rong Ge
MoMe
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Plateau in Monotonic Linear Interpolation -- A "Biased" View of Loss Landscape for Deep Networks"
7 / 7 papers shown
High-dimensional manifold of solutions in neural networks: insights from statistical physics
Enrico M. Malatesta
291
5
0
20 Feb 2025
Weight Scope Alignment: A Frustratingly Easy Method for Model Merging
European Conference on Artificial Intelligence (ECAI), 2024
Yichu Xu
Xin-Chun Li
Le Gan
De-Chuan Zhan
MoMe
293
2
0
22 Aug 2024
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
Derek Lim
Moe Putterman
Robin Walters
Haggai Maron
Stefanie Jegelka
471
15
0
30 May 2024
Manifold Metric: A Loss Landscape Approach for Predicting Model Performance
Pranshu Malviya
Jerry Huang
A. Baratin
Quentin Fournier
Sarath Chandar
268
0
0
24 May 2024
Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks
Yichu Xu
Xin-Chun Li
Lan Li
De-Chuan Zhan
328
2
0
21 May 2024
Exploring Neural Network Landscapes: Star-Shaped and Geodesic Connectivity
Zhanran Lin
Puheng Li
Lei Wu
456
9
0
09 Apr 2024
Transferring Learning Trajectories of Neural Networks
International Conference on Learning Representations (ICLR), 2023
Daiki Chijiwa
266
4
0
23 May 2023
1
