A $2$-closed permutation group with nonuniversal first-order invariant networks

We give a counterexample to a conjecture of Maron--Fetaya--Segol--Lipman on the universality of certain neural networks. More precisely let $G\cong S_6$ act on the $15$ unordered pairs of a six-element set. We show that this permutation group is $2$-closed, but every first-order $G$-invariant neural network, with arbitrary activation function, identifies the edge indicator vectors of a six-cycle and two disjoint triangle graphs. Since these vectors can be separated by a $G$-invariant cubic polynomial, we get that the latter cannot be approximated arbitrarily well by such neural networks.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-12
DOI
https://doi.org/10.5281/zenodo.24148289
Primary Topic
Neural Networks and Applications
Type
preprint
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preprint

A $2$-closed permutation group with nonuniversal first-order invariant networks

Ambrus Pál
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Applications
preprint

A $2$-closed permutation group with nonuniversal first-order invariant networks

Ambrus Pál
preprint en

Abstract

We give a counterexample to a conjecture of Maron--Fetaya--Segol--Lipman on the universality of certain neural networks. More precisely let $G\cong S_6$ act on the $15$ unordered pairs of a six-element set. We show that this permutation group is $2$-closed, but every first-order $G$-invariant neural network, with arbitrary activation function, identifies the edge indicator vectors of a six-cycle and two disjoint triangle graphs. Since these vectors can be separated by a $G$-invariant cubic polynomial, we get that the latter cannot be approximated arbitrarily well by such neural networks.

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Applications
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A $2$-closed permutation group with nonuniversal first-order invariant networks — Ambrus Pál · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS