Defines a positivity certificate for finite-sample identifiability of the control-channel block in Koopman EDMDc and derives closed-loop statistical bounds under behavior policies.
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Koopman-learned linear dynamics enable an online actor-critic RL method that improves sample efficiency and closed-loop performance on nonlinear robotic systems compared with model-free and other model-based baselines.
citing papers explorer
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Control-Channel Informativity for Koopman EDMDc under Behavior-Policy Data
Defines a positivity certificate for finite-sample identifiability of the control-channel block in Koopman EDMDc and derives closed-loop statistical bounds under behavior policies.
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Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems
Koopman-learned linear dynamics enable an online actor-critic RL method that improves sample efficiency and closed-loop performance on nonlinear robotic systems compared with model-free and other model-based baselines.