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Verisig 2.0: Verification of Neural Network Controllers Using Taylor Model Preconditioning
Lecture Notes in Computer Science
AbstractThis paper presents Verisig 2.0, a verification tool for closed-loop systems with neural network (NN) controllers. We focus on NNs with tanh/sigmoid activations and develop a Taylor-model-based reachability algorithm through Taylor model preconditioning and shrink wrapping. Furthermore, we provide a parallelized implementation that allows Verisig 2.0 to efficiently handle larger NNs than existing tools can. We provide an extensive evaluation over 10 benchmarks and compare Verisig 2.0doi:10.1007/978-3-030-81685-8_11 fatcat:ljm43ujxmzhd5dnxzavga7soqm