Equivariant Manifold FlowsDownload PDF

21 May 2021, 20:48 (modified: 28 Jan 2022, 04:22)NeurIPS 2021 PosterReaders: Everyone
Keywords: manifold, normalizing flow, equivariant, invariant
TL;DR: We construct manifold normalizing flows which are equivariant to isometric actions.
Abstract: Tractably modelling distributions over manifolds has long been an important goal in the natural sciences. Recent work has focused on developing general machine learning models to learn such distributions. However, for many applications these distributions must respect manifold symmetries—a trait which most previous models disregard. In this paper, we lay the theoretical foundations for learning symmetry-invariant distributions on arbitrary manifolds via equivariant manifold flows. We demonstrate the utility of our approach by learning quantum field theory-motivated invariant SU(n) densities and by correcting meteor impact dataset bias.
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Code: https://github.com/CUAI/Equivariant-Manifold-Flows
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