Software & Data Downloads — G-RepsNets

Group Representation Networks for general and efficient construction of equivariant neural networks using equivariant tensor polynomials and tensor mixing.

This is the code for the TMLR 2025 publication G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups. Given input representations and the group of interest, the work presents a general and efficient construction of equivariant neural networks using equivariant tensor polynomials and tensor mixing.

    •  Basu, S., Lohit, S., Brand, M., "G-RepsNet: A Lightweight Construction of Equivariant Net- works for Arbitrary Matrix Groups", Transactions on Machine Learning Research (TMLR), May 2025.
      BibTeX TR2025-056 PDF Software
      • @article{Basu2025may,
      • author = {Basu, Sourya and Lohit, Suhas and Brand, Matthew},
      • title = {{G-RepsNet: A Lightweight Construction of Equivariant Net- works for Arbitrary Matrix Groups}},
      • journal = {Transactions on Machine Learning Research (TMLR)},
      • year = 2025,
      • month = may,
      • url = {https://www.merl.com/publications/TR2025-056}
      • }

    Access software at https://github.com/merlresearch/G-RepsNets.