Autoencoding Dynamics: Topological Limitations and Capabilities

dc.contributor.authorKvalheim, Matthew D.
dc.contributor.authorSontag, Eduardo D.
dc.date.accessioned2026-01-06T20:51:44Z
dc.date.issued2025-11-11
dc.description.abstractGiven a “data manifold” M ⊂ Rⁿ and “latent space” R<superscript>ℓ</superscript>, an autoencoder is a pair ofcontinuous maps consisting of an “encoder” E : Rⁿ → R<superscript>ℓ</superscript>and “decoder” D : R<superscript>ℓ</superscript> → Rⁿ such that the “round trip” map D ◦ E|ₘ is as close as possible to the identity map idₘ on M. We present various topological limitations and capabilites inherent to the search for an autoencoder, and describe capabilities for autoencoding dynamical systems having M as an invariant manifold.
dc.description.sponsorshipThis material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-24-1-0299 (MK) and the Office of Naval Research under award number N00014-21-1-2431 (EDS). We thank Jeremy Jordan for alerting us to relevant statements made by [GBC16].
dc.description.urihttp://arxiv.org/abs/2511.04807
dc.format.extent23 pages
dc.genrejournal articles
dc.genrepreprints
dc.identifierdoi:10.13016/m2v1g1-abne
dc.identifier.urihttps://doi.org/10.48550/arXiv.2511.04807
dc.identifier.urihttp://hdl.handle.net/11603/41359
dc.language.isoen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectComputer Science - Machine Learning
dc.subjectMathematics - Dynamical Systems
dc.titleAutoencoding Dynamics: Topological Limitations and Capabilities
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-2662-6760

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