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-bound verifier and demonstrate how one of the current state-of-the-art branching heuristics, FSB, can be viewed as a special instantiation of the lookahead branching strategy.
arXiv:2607. 29051v1 Announce Type: cross Abstract: State-of-the-art neural network verifiers use the branch-and-bound procedure as their core solving mechanism.
By Liam Davis, Haoze Wu
arXiv:2607. 28954v1 Announce Type: new Abstract: Branch and Bound (BaB) aims to achieve complete verification of neural networks by adaptively partitioning the problem and applying off-the-shelf verifiers to subproblems.
By Jiawei Ren, Guanqin Zhang, Zhenya Zhang, Yulei Sui
arXiv:2609.25962v1 Announce Type: new
Abstract: Neural network verification has become a key tool for providing formal guarantees on the behaviour of neural networks. However, many verification probl...
By Annelot Bosman, Minghao Liu, Marta Kwiatkowska, Holger Hoos, Jan van Rijn
arXiv:2603. 23878v3 Announce Type: replace-cross Abstract: The parameterized CROWN analysis, a.
By Henry LeCates, Haoze Wu
arXiv:2503.12083v3 Announce Type: replace-cross
Abstract: Current Deep Neural Network (DNN) verifiers are typically designed to prioritize scalability over reliability. Reliability can be reinforced...
By Omri Isac, Idan Refaeli, Haoze Wu, Clark Barrett, Guy Katz