A framework for refining probabilistic zonotope disturbance models from trajectory data to compute less conservative reachable sets for linear systems with mixed bounded and Gaussian uncertainties.
Reachable set estimation for neural network control systems: A simulation-guided ap- proach,
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Reachability Analysis With Probabilistic Zonotopes: Learning Realized Disturbances and Refining Aleatory Uncertainty
A framework for refining probabilistic zonotope disturbance models from trajectory data to compute less conservative reachable sets for linear systems with mixed bounded and Gaussian uncertainties.