10 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Branch and Bound for Relational Verification of Neural Networks
Kota Fukuda, Zhenya Zhang, Guanqin Zhang +1
Verification of neural networks against relational specifications, such as global robustness, is crucial for safety-critical applications of cyber-physical systems (CPS), given the…
cs.LG2025★ 10 cited
Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
Guanqin Zhang, Kota Fukuda, Zhenya Zhang +4
The vulnerability of neural networks to adversarial perturbations has necessitated formal verification techniques that can rigorously certify the quality of neural networks. As the…
cs.LG2025
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
Kota Fukuda, Guanqin Zhang, Zhenya Zhang +2
Formal verification is a rigorous approach that can provably ensure the quality of neural networks, and to date, Branch and Bound (BaB) is the state-of-the-art that performs verifi…