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Incremental Neural Network Verification via Learned Conflicts
Raya Elsaleh, Liam Davis, Haoze Wu +1
Neural network verification is often used as a core component within larger analysis procedures, which generate sequences of closely related verification queries over the same netw…
Cubing for Tuning
Haoze Wu, Clark Barrett, Nina Narodytska
We are exploring the problem of building an automated reasoning procedure that adaptively tunes the high-level solving strategy for a given problem. There are two main distinctive…
PICID: Proof-Driven Clause Learning in Neural Network Verification
Omri Isac, Idan Refaeli, Haoze Wu +2
Current Deep Neural Network (DNN) verifiers are typically designed to prioritize scalability over reliability. Reliability can be reinforced through the generation of proofs that a…
Satisfiability Modulo Theories for Verifying MILP Certificates
Kenan Wood, Runtian Zhou, Haoze Wu +2
Correctness of results from mixed-integer linear programming (MILP) solvers is critical, particularly in the context of applications such as hardware verification, compiler optimiz…