Constrained matrix convex generators bridge data-driven reachability and statistical estimation by providing minimum-volume uncertainty sets that coincide with Gaussian maximum-likelihood ellipsoids and remain tighter than matrix zonotopes for mixed noise.
Reachability analysis and its application to the safety as- sessment of autonomous cars,
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Bridging Data-Driven Reachability Analysis and Statistical Estimation via Constrained Matrix Convex Generators
Constrained matrix convex generators bridge data-driven reachability and statistical estimation by providing minimum-volume uncertainty sets that coincide with Gaussian maximum-likelihood ellipsoids and remain tighter than matrix zonotopes for mixed noise.