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arXiv · 2609.00472

Higher Structures in Deep Learning

Michael L. Roberts·Carlos Zapata Carratalá. Nicholas J. Cooper·Lijun Chen·François G. Meyer·Danna Gurari
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Abstract

We provide an expository introduction on the importance of higher-arity tensor operations to deep learning. Then, we conduct a novel empirical investigation of higher-arity phenomenon in trained neural networks, introduce a hypergraphical generalization of the multilayer perceptron, and explore connections to evolutionary algorithms. We conclude with a discussion of promising directions for future research.

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Michael L. Roberts, Carlos Zapata Carratalá. Nicholas J. Cooper, Lijun Chen, François G. Meyer, Danna Gurari. 2026-08-31. Higher Structures in Deep Learning. https://arxiv.org/abs/2609.00472

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