Frame Averaging for Invariant and Equivariant Network Design
Omri Puny, Matan Atzmon, Heli Ben-Hamu, Ishan Misra, Aditya Grover, Edward J. Smith, Yaron Lipman
ICLR 2022. [Paper]
7 Oct 2021
Equivariance with Learned Canonicalization Functions
Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
ICML 2023. [Paper]
11 Nov 2022
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
Jinwoo Kim, Tien Dat Nguyen, Ayhan Suleymanzade, Hyeokjun An, Seunghoon Hong
NeurIPS 2023. [Paper]
5 Jun 2023
Smooth, exact rotational symmetrization for deep learning on point clouds
Sergey N. Pozdnyakov, Michele Ceriotti
NeurIPS 2023. [Paper]
30 May 2023
Learning Symmetrization for Equivariance with Orbit Distance Minimization
Tien Dat Nguyen*, Jinwoo Kim*, Hongseok Yang, Seunghoon Hong
NeurIPS 2023 Workshop. [Paper]
13 Nov 2023
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym*, Hannah Lawrence*, Jonathan W. Siegel*
ICML 2024. [Paper]
25 Feb 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji
ICML 2024. [Paper]
11 Jun 2024
A Canonization Perspective on Invariant and Equivariant Learning
George Ma*, Yifei Wang*, Derek Lim, Stefanie Jegelka, Yisen Wang
NeurIPS 2025. [Paper]
28 May 2024
Improving Equivariant Networks with Probabilistic Symmetry Breaking
Hannah Lawrence*, Vasco Portilheiro*, Yan Zhang, Sékou-Oumar Kaba
ICML 2024 Workshop. [Paper]
17 Jun 2024