Predicting trends in the quality of state-of-the-art neural networks
without access to training or testing data

Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data

17 February 2020

Charles H. Martin

Michael W. Mahoney

Papers citing "Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data"

18 / 18 papers shown

Title
A Model Zoo on Phase Transitions in Neural Networks Konstantin Schurholt Léo Meynent Yefan Zhou Haiquan Lu Yaoqing Yang Damian Borth 68 0 0 25 Apr 2025
Regional Tiny Stories: Using Small Models to Compare Language Learning and Tokenizer Performance Nirvan Patil Malhar Abhay Inamdar Agnivo Gosai Guruprasad Pathak Anish Joshi Aryan Sagavekar Anish Joshirao Raj Abhijit Dandekar Rajat Dandekar Sreedath Panat 44 0 0 07 Apr 2025
Mitigating Memorization In Language Models Mansi Sakarvadia Aswathy Ajith Arham Khan Nathaniel Hudson Caleb Geniesse Kyle Chard Yaoqing Yang Ian Foster Michael W. Mahoney KELM MU 55 0 0 03 Oct 2024
Talking Heads: Understanding Inter-layer Communication in Transformer Language Models Jack Merullo Carsten Eickhoff Ellie Pavlick 56 13 0 13 Jun 2024
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 20 7 0 15 Jul 2023
Heavy-Tailed Regularization of Weight Matrices in Deep Neural Networks Xuanzhe Xiao Zengyi Li Chuanlong Xie Fengwei Zhou 21 3 0 06 Apr 2023
Deep Learning Weight Pruning with RMT-SVD: Increasing Accuracy and Reducing Overfitting Yitzchak Shmalo Jonathan Jenkins Oleksii Krupchytskyi 22 3 0 15 Mar 2023
Multi-Object Navigation with dynamically learned neural implicit representations Pierre Marza L. Matignon Olivier Simonin Christian Wolf 27 23 0 11 Oct 2022
Extended critical regimes of deep neural networks Chengqing Qu Asem Wardak P. Gong AI4CE 19 1 0 24 Mar 2022
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 21 32 0 17 Feb 2022
Investigating Power laws in Deep Representation Learning Arna Ghosh Arnab Kumar Mondal Kumar Krishna Agrawal Blake A. Richards SSL OOD 11 19 0 11 Feb 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 86 17 0 06 Feb 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Z. Ringel 30 49 0 31 Dec 2021
Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping Xuran Meng Jianfeng Yao 17 7 0 26 Nov 2021
Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics Charles H. Martin Michael W. Mahoney 13 19 0 01 Jun 2021
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018
Cleaning large correlation matrices: tools from random matrix theory J. Bun J. Bouchaud M. Potters 29 262 0 25 Oct 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015