Sparse Koopman Autoencoders Identify Local Dynamical Regimes in Multibasin Systems
Koopman autoencoders (KAEs) seek a higher-dimensional latent representation in which nonlinear dynamics evolve linearly. However, many interesting systems have multiple basins of attraction, and both theoretical and empirical work has shown these multibasin systems cannot generally admit a single finite-dimensional global Koopman embedding under standard assumptions. We posit that encoders with a sparsity-inducing objective encouraging few active latent coefficients will provide latent supports as an inspectable basin-modeling principle for Koopman autoencoders. We use these encoders producing sparse latents in training Sparse Koopman Autoencoders (SKAEs) without basin labels or other reg...
| Authors | Aidan Li, Uday Kiran Reddy Tadipatri, Mahan Fathi et al. |
|---|---|
| Primary category | cs.LG |
| Published | 29 August 2026 |
| Last updated at source | 13 October 2026 |
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