Higher Structures in Deep Learning

Michael L. Roberts, Carlos Zapata Carratalá. Nicholas J. Cooper, Lijun Chen, François G. Meyer, Danna Gurari
8/31/2026
cs.LGcs.AI

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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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Cite this paper

@article{roberts2026higher,
  title  = {Higher Structures in Deep Learning},
  author = {Michael L. Roberts and Carlos Zapata Carratalá. Nicholas J. Cooper and Lijun Chen and François G. Meyer and Danna Gurari},
  year   = {2026},
  eprint = {2609.00472},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2609.00472v1}
}

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