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arXiv · 2212.08648

Connecting Permutation Equivariant Neural Networks and Partition Diagrams

Edward Pearce-Crump
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Abstract

Permutation equivariant neural networks are often constructed using tensor powers of $\mathbb{R}^{n}$ as their layer spaces. We show that all of the weight matrices that appear in these neural networks can be obtained from Schur-Weyl duality between the symmetric group and the partition algebra. In particular, we adapt Schur-Weyl duality to derive a simple, diagrammatic method for calculating the weight matrices themselves.

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Edward Pearce-Crump. 2022-12-16. Connecting Permutation Equivariant Neural Networks and Partition Diagrams. https://arxiv.org/abs/2212.08648

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