Paper
Higher Structures in Deep Learning
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. · Authors: Michael L. Roberts, Carlos Zapata Carratalá. Nicholas J. Cooper, Lijun Chen, François G. Meyer, Danna Gurari · Published 2026-08-31 · arXiv:2609.00472
- Published
- 2026-08-31
- Authors
- 5
- arXiv
- 2609.00472
- Category
- cs.LG
Abstract
arXiv:2609.00472
Michael L. Roberts, Carlos Zapata Carratalá. Nicholas J. Cooper, Lijun Chen, François G. Meyer, Danna Gurari
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.