Predicting Neural Network Accuracy from Weights

26 February 2020

Papers citing "Predicting Neural Network Accuracy from Weights"

22 / 22 papers shown

Title
A Model Zoo on Phase Transitions in Neural Networks Konstantin Schurholt Léo Meynent Yefan Zhou Haiquan Lu Yaoqing Yang Damian Borth 63 0 0 25 Apr 2025
Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space Vinicius Hernandes Thomas Spriggs Saqar Khaleefah E. Greplova 47 0 0 21 Mar 2025
Adversarial Robustness in Parameter-Space Classifiers Tamir Shor Ethan Fetaya Chaim Baskin A. Bronstein AAML OOD 141 0 0 27 Feb 2025
Monomial Matrix Group Equivariant Neural Functional Networks Hoang V. Tran Thieu N. Vo Tho H. Tran An T. Nguyen Tan M. Nguyen 54 5 0 18 Sep 2024
Unleash Graph Neural Networks from Heavy Tuning Lequan Lin Dai Shi Andi Han Zhiyong Wang Junbin Gao AI4CE 27 2 0 21 May 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift Renchunzi Xie Ambroise Odonnat Vasilii Feofanov I. Redko Jianfeng Zhang Bo An UQCV 70 1 0 17 Jan 2024
Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim Haggai Maron Marc T. Law Jonathan Lorraine James Lucas AI4CE 29 30 0 07 Dec 2023
Equivariant Deep Weight Space Alignment Aviv Navon Aviv Shamsian Ethan Fetaya Gal Chechik Nadav Dym Haggai Maron 21 21 0 20 Oct 2023
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models D. Honegger Konstantin Schurholt Damian Borth 20 4 0 26 Apr 2023
Deep Learning on Implicit Neural Representations of Shapes Luca de Luigi Adriano Cardace Riccardo Spezialetti Pierluigi Zama Ramirez Samuele Salti Luigi Di Stefano 19 46 0 10 Feb 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 30 63 0 30 Jan 2023
Privacy and Efficiency of Communications in Federated Split Learning Zongshun Zhang Andrea Pinto Valeria Turina Flavio Esposito I. Matta FedML 19 32 0 04 Jan 2023
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 24 14 0 13 Dec 2022
Multi-Object Navigation with dynamically learned neural implicit representations Pierre Marza L. Matignon Olivier Simonin Christian Wolf 27 23 0 11 Oct 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 26 16 0 14 Jul 2022
Leveraging the Graph Structure of Neural Network Training Dynamics Fatemeh Vahedian Ruiyu Li Puja Trivedi Di Jin Danai Koutra AI4CE GNN 19 3 0 09 Nov 2021
Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Konstantin Schurholt Dimche Kostadinov Damian Borth SSL 19 14 0 28 Oct 2021
In Search of Probeable Generalization Measures Jonathan Jaegerman Khalil Damouni M. M. Ankaralı Konstantinos N. Plataniotis 11 2 0 23 Oct 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 17 155 0 17 Jun 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? Weijian Deng Stephen Gould Liang Zheng 19 62 0 10 Jun 2021
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks Konstantin Schurholt Damian Borth 16 3 0 18 Jun 2020
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 114 577 0 27 Feb 2015