Classifying the classifier: dissecting the weight space of neural networks

13 February 2020

Timo Ropinski

Anders Ynnerman

Papers citing "Classifying the classifier: dissecting the weight space of neural networks"

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 70 0 0 25 Apr 2025
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion Rana Muhammad Shahroz Khan Dongwen Tang Pingzhi Li Kai Wang Tianlong Chen AI4CE 220 0 0 31 Mar 2025
Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space Vinicius Hernandes Thomas Spriggs Saqar Khaleefah E. Greplova 52 1 0 21 Mar 2025
Adversarial Robustness in Parameter-Space Classifiers Tamir Shor Ethan Fetaya Chaim Baskin A. Bronstein AAML OOD 252 0 0 27 Feb 2025
Model Lakes Koyena Pal David Bau Renée J. Miller 67 0 0 24 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
Towards Scalable and Versatile Weight Space Learning Konstantin Schurholt Michael W. Mahoney Damian Borth 52 16 0 14 Jun 2024
Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim Haggai Maron Marc T. Law Jonathan Lorraine James Lucas AI4CE 36 31 0 07 Dec 2023
Equivariant Deep Weight Space Alignment Aviv Navon Aviv Shamsian Ethan Fetaya Gal Chechik Nadav Dym Haggai Maron 35 21 0 20 Oct 2023
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models D. Honegger Konstantin Schurholt Damian Borth 37 4 0 26 Apr 2023
Permutation Equivariant Neural Functionals Allan Zhou Kaien Yang Kaylee Burns Adriano Cardace Yiding Jiang Samuel Sokota J. Zico Kolter Chelsea Finn 35 47 0 27 Feb 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 49 63 0 30 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 40 14 0 13 Dec 2022
Model Zoos: A Dataset of Diverse Populations of Neural Network Models Konstantin Schurholt Diyar Taskiran Boris Knyazev Xavier Giró-i-Nieto Damian Borth 60 29 0 29 Sep 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 34 16 0 14 Jul 2022
Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Konstantin Schurholt Dimche Kostadinov Damian Borth SSL 41 14 0 28 Oct 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? Weijian Deng Stephen Gould Liang Zheng 39 63 0 10 Jun 2021
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 14 56 0 14 Aug 2020
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks Konstantin Schurholt Damian Borth 32 3 0 18 Jun 2020
Predicting Neural Network Accuracy from Weights Thomas Unterthiner Daniel Keysers Sylvain Gelly Olivier Bousquet Ilya O. Tolstikhin 30 101 0 26 Feb 2020
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data Charles H. Martin Tongsu Peng Peng Michael W. Mahoney 36 101 0 17 Feb 2020
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 274 5,331 0 05 Nov 2016