3 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Lookahead Branching for Neural Network Verification
Liam Davis, Duo Zhou, Huan Zhang +3
In this work, we investigate the effect of lookahead branching strategies in neural network verification. We present a general recipe to integrate lookahead into any branch-and-bou…
E-Globe: Scalable -Global Verification of Neural Networks via Tight Upper Bounds and Pattern-Aware Branching
Wenting Li, Saif R. Kazi, Russell Bent +2
Neural networks achieve strong empirical performance, but robustness concerns still hinder deployment in safety-critical applications. Formal verification provides robustness guara…
Clip-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verification
Duo Zhou, Jorge Chavez, Hesun Chen +2
State-of-the-art neural network (NN) verifiers demonstrate that applying the branch-and-bound (BaB) procedure with fast bounding techniques plays a key role in tackling many challe…
Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes
Duo Zhou, Christopher Brix, Grani A Hanasusanto +1
Recently, cutting-plane methods such as GCP-CROWN have been explored to enhance neural network verifiers and made significant advances. However, GCP-CROWN currently relies on gener…