Graph Neural Networks for Learning Equivariant Representations of Neural
Networks

Graph Neural Networks for Learning Equivariant Representations of Neural Networks

18 March 2024

Miltiadis Kofinas

Boris Knyazev

Gertjan J. Burghouts

Cees G. M. Snoek

Papers citing "Graph Neural Networks for Learning Equivariant Representations of Neural Networks"

10 / 10 papers shown

Title
Learning Versatile Optimizers on a Compute Diet A. Moudgil Boris Knyazev Guillaume Lajoie Eugene Belilovsky 66 0 0 22 Jan 2025
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations Yonatan Sverdlov Ido Springer Nadav Dym 29 2 0 09 Oct 2024
Monomial Matrix Group Equivariant Neural Functional Networks Hoang V. Tran Thieu N. Vo Tho H. Tran An T. Nguyen Tan M. Nguyen 49 5 0 18 Sep 2024
Grounding Continuous Representations in Geometry: Equivariant Neural Fields David R. Wessels David M. Knigge Samuele Papa Riccardo Valperga Sharvaree P. Vadgama E. Gavves Erik J. Bekkers 33 7 0 09 Jun 2024
Model Zoos: A Dataset of Diverse Populations of Neural Network Models Konstantin Schurholt Diyar Taskiran Boris Knyazev Xavier Giró-i-Nieto Damian Borth 44 29 0 29 Sep 2022
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights Konstantin Schurholt Boris Knyazev Xavier Giró-i-Nieto Damian Borth 48 38 0 29 Sep 2022
Learning to Learn with Generative Models of Neural Network Checkpoints William S. Peebles Ilija Radosavovic Tim Brooks Alexei A. Efros Jitendra Malik UQCV 73 64 0 26 Sep 2022
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases James Harrison Luke Metz Jascha Narain Sohl-Dickstein 42 22 0 22 Sep 2022
From data to functa: Your data point is a function and you can treat it like one Emilien Dupont Hyunjik Kim S. M. Ali Eslami Danilo Jimenez Rezende Dan Rosenbaum TDI 3DPC 162 136 0 28 Jan 2022
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 166 1,095 0 27 Apr 2021