45 citations · 97 across the 32 of their papers we have counts for
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stat.ML2020★ 6 cited
Universal Approximation Theorem for Equivariant Maps by Group CNNs
Wataru Kumagai, Akiyoshi Sannai
Group symmetry is inherent in a wide variety of data distributions. Data processing that preserves symmetry is described as an equivariant map and often effective in achieving high…
stat.ML2019★ 4 cited
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…
stat.ML2018★ 5 cited
Reconstruction of training samples from loss functions
Akiyoshi Sannai
This paper presents a new mathematical framework to analyze the loss functions of deep neural networks with ReLU functions. Furthermore, as as application of this theory, we prove…