mlsanityData to 14 Oct 2026

Deep belief networks are exact

arXiv 2609.05572 ↗First posted 4 Sep 2026cs.AI cs.LG math.PRcited by 0

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Abstract (arXiv)

We prove that every strictly positive probability distribution on (-1,1n) is represented exactly by a sigmoid belief network with finite parameters. This answers a question of Sutskever and Hinton. The proof upgrades their probability-sharing approximation to exact representation using Brouwer's fixed-point theorem.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 8 references that are in the map. First posted on arXiv 4 Sep 2026.

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References · 1

  1. 2019Stochastic Feedforward Neural Networks: Universal Approximationcited by 7

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