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Learning Useful Representations of Recurrent Neural Network Weight Matrices
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Learning Useful Representations of Recurrent Neural Network Weight Matrices

International Conference on Machine Learning (ICML), 2024
Vincent Herrmann
Francesco Faccio
Jürgen Schmidhuber
ArXiv (abs)PDFHTML

Papers citing "Learning Useful Representations of Recurrent Neural Network Weight Matrices"

7 / 7 papers shown
Title
Learning Model Representations Using Publicly Available Model Hubs
Learning Model Representations Using Publicly Available Model Hubs
Damian Falk
Konstantin Schürholt
Konstantinos Tzevelekakis
Léo Meynent
Damian Borth
3DH
108
0
0
02 Oct 2025
GradMetaNet: An Equivariant Architecture for Learning on Gradients
GradMetaNet: An Equivariant Architecture for Learning on Gradients
Yoav Gelberg
Yam Eitan
Aviv Navon
Aviv Shamsian
Theo
Putterman
Michael M. Bronstein
Haggai Maron
71
1
0
02 Jul 2025
A Model Zoo on Phase Transitions in Neural Networks
A Model Zoo on Phase Transitions in Neural Networks
Konstantin Schurholt
Léo Meynent
Yefan Zhou
Haiquan Lu
Yaoqing Yang
Damian Borth
210
2
0
25 Apr 2025
The Impact of Model Zoo Size and Composition on Weight Space Learning
The Impact of Model Zoo Size and Composition on Weight Space Learning
Damian Falk
Konstantin Schurholt
Damian Borth
207
1
0
14 Apr 2025
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction
Léo Meynent
Ivan Melev
Konstantin Schurholt
Göran Kauermann
Damian Borth
221
5
0
21 Mar 2025
Local and Global Decoding in Text Generation
Local and Global Decoding in Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Daniel Gareev
Thomas Hofmann
Ezhilmathi Krishnasamy
Tiago Pimentel
174
3
0
14 Oct 2024
Improved Generalization of Weight Space Networks via Augmentations
Improved Generalization of Weight Space Networks via Augmentations
Aviv Shamsian
Aviv Navon
David W. Zhang
Yan Zhang
Ethan Fetaya
Gal Chechik
Haggai Maron
166
16
0
06 Feb 2024

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