Gives necessary and sufficient exactness certificates based on primal and dual feasibility for when a violated-set closed-form correction equals the exact Euclidean projection in CBF safety filters.
53rd IEEE conference on decision and control , pages=
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LightCROWN computes tighter Jacobian bounds for neural networks with smooth nonlinear activations by exploiting their analytical properties, raising verification success rates for neural control barrier functions up to 100% on benchmark control systems.
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Exactness Certificates for Closed-Form CBF Safety-Filter Projections
Gives necessary and sufficient exactness certificates based on primal and dual feasibility for when a violated-set closed-form correction equals the exact Euclidean projection in CBF safety filters.
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Efficient Verification of Neural Control Barrier Functions with Smooth Nonlinear Activations
LightCROWN computes tighter Jacobian bounds for neural networks with smooth nonlinear activations by exploiting their analytical properties, raising verification success rates for neural control barrier functions up to 100% on benchmark control systems.