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Keyan Miao

2 accepted papers

2026

Learning Koopman Representations with Controllability Guarantees

ICLR 2026poster

Learning nonlinear dynamical models from data is central to control. Two fundamental challenges exist: (1) how to learn accurate models from limited data, and (2) how to ensure the learned models are suitable for control design of the nominal system. We address both by enforcing a critical \emph{a p…

Cited by 0SourceScholar
2024

How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective

ICML 2024poster

Neural Ordinary Differential Equations (ODEs) have shown promise in learning continuous dynamics. However, their slow training and inference speed hinder wider applications. In this paper, we propose to optimize Neural ODEs from a spatial and temporal perspective, drawing inspiration from control th…

Cited by 2SourcePDFScholar