Tag
The paper introduces a branch-and-bound framework for scalable verification of nonlinear neural feedback systems, improving state-of-the-art methods by combining combinatorial and propagative solvers through tools like rail and clipper.
This paper presents a methodology for determining the longest straight-line paths on Earth that avoid land or major water bodies, using a branch-and-bound algorithm to tackle optimization challenges.
This paper introduces an inprocessing framework for neural network verification driven by lookahead lemmas, improving the performance of verifiers Marabou and α-β-CROWN by proving up to 34% more instances unsatisfiable.
This paper proposes efficient search methods to locate verdict boundaries in Branch and Bound (BaB) neural network verification, leveraging path monotonicity to skip irrelevant subproblems and improve verification efficiency.