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Found 5 papers, 2 papers with code
Deep Hankel matrices with random elements
Willems' fundamental lemma enables a trajectory-based characterization of linear systems through data-based Hankel matrices.
Produce Once, Utilize Twice for Anomaly Detection
Equipped with the above modules, POUTA is endowed with the ability to provide a more precise anomaly location than the prior arts.
Ranked #16 on
Anomaly Detection
on MVTec AD
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
For the training of reinforcement learning agents, the set of all stable linear operators is given explicitly through a matrix factorization approach.
Reinforcement Learning with Partial Parametric Model Knowledge
We adapt reinforcement learning (RL) methods for continuous control to bridge the gap between complete ignorance and perfect knowledge of the environment.
A modular framework for stabilizing deep reinforcement learning control
We propose a framework for the design of feedback controllers that combines the optimization-driven and model-free advantages of deep reinforcement learning with the stability guarantees provided by using the Youla-Kucera parameterization to define the search domain.
