Geometric Newton-polytope formulation of the maximal-ReLU-function conjecture

Let Δ(m)\Delta(m) be the recursively defined collection of network polytopes with mm hidden layers, and let N(f)\mathcal{N}(f) denote the Newton polytope of a positively homogeneous CPWL function ff. Set

m=log2(n+1)1.m=\lceil\log_2(n+1)\rceil-1.

Hertrich et al.'s geometric conjecture. There do not exist polytopes P,QΔ(m)P,Q\in\Delta(m) such that

P=N(max{x1,x2,,xn,0})+Q.P=\mathcal{N}\bigl(\max\{x_1,x_2,\ldots,x_n,0\}\bigr)+Q.

This is described as an equivalent geometric formulation of the conjecture that the displayed maximal function requires depth log2(n+1)\lceil\log_2(n+1)\rceil. Its general status is open.

Sources & referencesView supporting material

Primary source

Juan L. Valerdi, “On Minimal Depth in Neural Networks”, arXiv:2402.15315 (2026).

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