6 citations · 7 across the 4 of their papers we have counts for
4 papers
Efficiently Computing Compact Formal Explanations
Min Wu, Xiaofu Li, Haoze Wu +1
Building on VeriX (Verified eXplainability, arXiv:2212.01051), a system for producing optimal verified explanations for machine learning models, we present VeriX+, which significan…
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
Haoze Wu, Omri Isac, Aleksandar Zeljić +14
This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool's architectural design a…
Towards Efficient Verification of Quantized Neural Networks
Pei Huang, Haoze Wu, Yuting Yang +4
Quantization replaces floating point arithmetic with integer arithmetic in deep neural network models, providing more efficient on-device inference with less power and memory. In t…
Soy: An Efficient MILP Solver for Piecewise-Affine Systems
Haoze Wu, Min Wu, Dorsa Sadigh +1
Piecewise-affine (PWA) systems are widely used for modeling and control of robotics problems including modeling contact dynamics. A common approach is to encode the control problem…