autonomous vehicles 1bayesian meta-learning 1distribution shift 1dynamics modeling 1koopman operators 1uncertainty quantification 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
MetaKoopman: Bayesian Meta-Learning of Koopman Operators for Modeling Structured Dynamics under Distribution Shifts
Mahmoud Selim, Sriharsha Bhat, Karl H. Johansson
MetaKoopman is a Bayesian meta‑learning framework that learns a prior over Koopman operators to model nonlinear dynamics with linear latent representations, providing closed‑form u…
cs.LG2025
Federated Flow Matching
Zifan Wang, Anqi Dong, Mahmoud Selim +2
Data today is decentralized, generated and stored across devices and institutions where privacy, ownership, and regulation prevent centralization. This motivates the need to train…