A property-driven adaptive time-step reachability algorithm for linear continuous systems that uses safety properties to enable larger steps and fewer iterations than error-driven or fixed-step methods, with optimizations for matrix exponentials and error balancing.
In: Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and Control
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VNN-LIB 2.0 defines a network theory abstraction, formal query syntax, type system over numeric domains, and Agda-mechanized semantics to provide rigorous foundations for neural network verification independent of evolving model formats.
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VNN-LIB 2.0: Rigorous Foundations for Neural Network Verification
VNN-LIB 2.0 defines a network theory abstraction, formal query syntax, type system over numeric domains, and Agda-mechanized semantics to provide rigorous foundations for neural network verification independent of evolving model formats.