45 citations · 97 across the 32 of their papers we have counts for
3 papers · 1 filter
Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces
Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano
Numerous invariant (or equivariant) neural networks have succeeded in handling invariant data such as point clouds and graphs. However, a generalization theory for the neural netwo…
Asymptotic Risk of Bezier Simplex Fitting
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi +1
The Bezier simplex fitting is a novel data modeling technique which exploits geometric structures of data to approximate the Pareto front of multi-objective optimization problems.…
Universal approximations of permutation invariant/equivariant functions by deep neural networks
Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
In this paper, we develop a theory about the relationship between -invariant/equivariant functions and deep neural networks for finite group . Especially, for a given -inv…