Autoencoding Dynamics: Topological Limitations and Capabilities
Given a "data manifold" $M\subset \mathbb{R}^n$ and "latent space" $\mathbb{R}^\ell$, an autoencoder is a pair of continuous maps consisting of an "encoder" $E\colon \mathbb{R}^n\to \mathbb{R}^\ell$ and "decoder" $D\colon \mathbb{R}^\ell\to \mathbb{R}^n$ such that the "round trip" map $D\circ E$ is as close as possible to the identity map $\mbox{id}_M$ 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.
Authors
- Eduardo D. Sontag (ORCID: https://orcid.org/0000-0001-8020-5783)
- Matthew D. Kvalheim (ORCID: https://orcid.org/0000-0002-2662-6760)
Publication Details
- Journal
- Maryland Shared Open Access Repository (USMAI Consortium)
- Published
- 2025-11-11
- DOI
- https://doi.org/10.13016/m2v1g1-abne
- Primary Topic
- Topological and Geometric Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00