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The Impact of Model Zoo Size and Composition on Weight Space Learning

The Impact of Model Zoo Size and Composition on Weight Space Learning

14 April 2025
Damian Falk
Konstantin Schurholt
Damian Borth
ArXiv (abs)PDFHTML

Papers citing "The Impact of Model Zoo Size and Composition on Weight Space Learning"

38 / 38 papers shown
Title
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
111
3
0
21 Mar 2025
Towards Scalable and Versatile Weight Space Learning
Towards Scalable and Versatile Weight Space Learning
Konstantin Schurholt
Michael W. Mahoney
Damian Borth
98
19
0
14 Jun 2024
Transferring Knowledge from Large Foundation Models to Small Downstream
  Models
Transferring Knowledge from Large Foundation Models to Small Downstream Models
Shikai Qiu
Boran Han
Danielle C. Maddix
Shuai Zhang
Yuyang Wang
Andrew Gordon Wilson
45
3
0
11 Jun 2024
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Cristian Rodriguez-Opazo
Ehsan Abbasnejad
Damien Teney
Edison Marrese-Taylor
Hamed Damirchi
Anton Van Den Hengel
VLM
96
1
0
27 May 2024
The Platonic Representation Hypothesis
The Platonic Representation Hypothesis
Minyoung Huh
Brian Cheung
Tongzhou Wang
Phillip Isola
115
141
0
13 May 2024
Learning Useful Representations of Recurrent Neural Network Weight
  Matrices
Learning Useful Representations of Recurrent Neural Network Weight Matrices
Vincent Herrmann
Francesco Faccio
Jürgen Schmidhuber
61
7
0
18 Mar 2024
Training-Free Pretrained Model Merging
Training-Free Pretrained Model Merging
Zhenxing Xu
Ke Yuan
Huiqiong Wang
Yong Wang
Mingli Song
Mingli Song
MoMe
85
17
0
04 Mar 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
95
14
0
06 Feb 2024
Graph Metanetworks for Processing Diverse Neural Architectures
Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim
Haggai Maron
Marc T. Law
Jonathan Lorraine
James Lucas
AI4CE
77
39
0
07 Dec 2023
Equivariant Deep Weight Space Alignment
Equivariant Deep Weight Space Alignment
Aviv Navon
Aviv Shamsian
Ethan Fetaya
Gal Chechik
Nadav Dym
Haggai Maron
62
24
0
20 Oct 2023
Can We Scale Transformers to Predict Parameters of Diverse ImageNet
  Models?
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Boris Knyazev
Doha Hwang
Simon Lacoste-Julien
AI4CE
81
21
0
07 Mar 2023
Permutation Equivariant Neural Functionals
Permutation Equivariant Neural Functionals
Allan Zhou
Kaien Yang
Kaylee Burns
Adriano Cardace
Yiding Jiang
Samuel Sokota
J. Zico Kolter
Chelsea Finn
90
56
0
27 Feb 2023
Equivariant Architectures for Learning in Deep Weight Spaces
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon
Aviv Shamsian
Idan Achituve
Ethan Fetaya
Gal Chechik
Haggai Maron
95
69
0
30 Jan 2023
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution
  Generalization
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
Alexandre Ramé
Kartik Ahuja
Jianyu Zhang
Matthieu Cord
Léon Bottou
David Lopez-Paz
MoMeOODD
99
86
0
20 Dec 2022
Deep Model Reassembly
Deep Model Reassembly
Xingyi Yang
Zhou Daquan
Songhua Liu
Jingwen Ye
Xinchao Wang
MoMe
87
129
0
24 Oct 2022
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
Konstantin Schurholt
Diyar Taskiran
Boris Knyazev
Xavier Giró-i-Nieto
Damian Borth
126
30
0
29 Sep 2022
Hyper-Representations as Generative Models: Sampling Unseen Neural
  Network Weights
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Konstantin Schurholt
Boris Knyazev
Xavier Giró-i-Nieto
Damian Borth
120
42
0
29 Sep 2022
Learning to Learn with Generative Models of Neural Network Checkpoints
Learning to Learn with Generative Models of Neural Network Checkpoints
William S. Peebles
Ilija Radosavovic
Tim Brooks
Alexei A. Efros
Jitendra Malik
UQCV
150
68
0
26 Sep 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries
Git Re-Basin: Merging Models modulo Permutation Symmetries
Samuel K. Ainsworth
J. Hayase
S. Srinivasa
MoMe
298
344
0
11 Sep 2022
Factorizing Knowledge in Neural Networks
Factorizing Knowledge in Neural Networks
Xingyi Yang
Jingwen Ye
Xinchao Wang
MoMe
102
125
0
04 Jul 2022
Learning the Space of Deep Models
Learning the Space of Deep Models
G. Berardi
Luca de Luigi
Samuele Salti
Luigi Di Stefano
SSL
51
3
0
10 Jun 2022
Model soups: averaging weights of multiple fine-tuned models improves
  accuracy without increasing inference time
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Mitchell Wortsman
Gabriel Ilharco
S. Gadre
Rebecca Roelofs
Raphael Gontijo-Lopes
...
Hongseok Namkoong
Ali Farhadi
Y. Carmon
Simon Kornblith
Ludwig Schmidt
MoMe
161
1,009
1
10 Mar 2022
Parameter Prediction for Unseen Deep Architectures
Parameter Prediction for Unseen Deep Architectures
Boris Knyazev
M. Drozdzal
Graham W. Taylor
Adriana Romero Soriano
OOD
97
83
0
25 Oct 2021
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting
  Model Hubs
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs
Kaichao You
Yong Liu
Ziyang Zhang
Jianmin Wang
Michael I. Jordan
Mingsheng Long
187
33
0
20 Oct 2021
Robust fine-tuning of zero-shot models
Robust fine-tuning of zero-shot models
Mitchell Wortsman
Gabriel Ilharco
Jong Wook Kim
Mike Li
Simon Kornblith
...
Raphael Gontijo-Lopes
Hannaneh Hajishirzi
Ali Farhadi
Hongseok Namkoong
Ludwig Schmidt
VLM
158
739
0
04 Sep 2021
Zoo-Tuning: Adaptive Transfer from a Zoo of Models
Zoo-Tuning: Adaptive Transfer from a Zoo of Models
Yang Shu
Zhi Kou
Zhangjie Cao
Jianmin Wang
Mingsheng Long
62
44
0
29 Jun 2021
How to train your ViT? Data, Augmentation, and Regularization in Vision
  Transformers
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
Andreas Steiner
Alexander Kolesnikov
Xiaohua Zhai
Ross Wightman
Jakob Uszkoreit
Lucas Beyer
ViT
125
635
0
18 Jun 2021
Factors of Influence for Transfer Learning across Diverse Appearance
  Domains and Task Types
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types
Thomas Mensink
J. Uijlings
Alina Kuznetsova
Michael Gygli
V. Ferrari
VLM
96
84
0
24 Mar 2021
Predicting Neural Network Accuracy from Weights
Predicting Neural Network Accuracy from Weights
Thomas Unterthiner
Daniel Keysers
Sylvain Gelly
Olivier Bousquet
Ilya O. Tolstikhin
69
107
0
26 Feb 2020
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
Charles H. Martin
Tongsu Peng
Peng
Michael W. Mahoney
90
110
0
17 Feb 2020
Classifying the classifier: dissecting the weight space of neural
  networks
Classifying the classifier: dissecting the weight space of neural networks
Gabriel Eilertsen
Daniel Jonsson
Timo Ropinski
Jonas Unger
Anders Ynnerman
59
54
0
13 Feb 2020
Traditional and Heavy-Tailed Self Regularization in Neural Network
  Models
Traditional and Heavy-Tailed Self Regularization in Neural Network Models
Charles H. Martin
Michael W. Mahoney
79
126
0
24 Jan 2019
Graph HyperNetworks for Neural Architecture Search
Graph HyperNetworks for Neural Architecture Search
Chris Zhang
Mengye Ren
R. Urtasun
GNN
76
280
0
12 Oct 2018
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and
  Land Cover Classification
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification
P. Helber
B. Bischke
Andreas Dengel
Damian Borth
156
1,834
0
31 Aug 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
285
8,926
0
25 Aug 2017
HyperNetworks
HyperNetworks
David R Ha
Andrew M. Dai
Quoc V. Le
170
1,633
0
27 Sep 2016
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
367
19,745
0
09 Mar 2015
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
236
8,353
0
06 Nov 2014
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