Discovering Latent Response Laws in Forced Physical Systems
Governing equations provide compact descriptions of physical systems, yet the variables in which they are simple are often hidden in high-dimensional measurements. This challenge is sharper for forced systems, whose responses depend on both intrinsic dynamics and time-dependent inputs. Here we introduce FLARE, a forced latent autoencoder for response equations that learns compact response coordinates, identifies sparse input-dependent latent dynamics and decodes equation rollouts to full responses. By estimating latent dimension from data and separating state estimation from external forcing, FLARE enables forecasts to be initialized from past responses and driven by prescribed future inp...
| Authors | Yi Zhu, Su Chen, Xiaojun Li et al. |
|---|---|
| Primary category | cs.LG |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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