Brauer's Group Equivariant Neural Networks

Jul 24, 2023



We provide a full characterisation of all of the possible group equivariant neural networks whose layers are some tensor power of ℝ^n for three symmetry groups that are missing from the machine learning literature: O(n), the orthogonal group; SO(n), the special orthogonal group; and Sp(n), the symplectic group. In particular, we find a spanning set of matrices for the learnable, linear, equivariant layer functions between such tensor power spaces in the standard basis of ℝ^n when the group is O(n) or SO(n), and in the symplectic basis of ℝ^n when the group is Sp(n).


Store presentation

Should this presentation be stored for 1000 years?

How do we store presentations

Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%


Recommended Videos

Presentations on similar topic, category or speaker

Interested in talks like this? Follow ICML 2023