Haoze Wu

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 42

Top Topics

Top Venues

Publications

Udayan Mandal, Guy Amir, Haoze Wu, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates. CoRR (2024)
Haoze Wu, Clark W. Barrett, Nina Narodytska
Lemur: Integrating Large Language Models in Automated Program Verification. ICLR (2024)
Udayan Mandal, Guy Amir, Haoze Wu, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Kerianne Hobbs, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
Safe and Reliable Training of Learning-Based Aerospace Controllers. CoRR (2024)
Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu, Yedi Zhang, Clark W. Barrett
Towards Efficient Verification of Quantized Neural Networks. AAAI (2024)
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. CAV (2) (2024)
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. CoRR (2024)
Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning. CoRR (2023)
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
Convex Bounds on the Softmax Function with Applications to Robustness Verification. CoRR (2023)
Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer
Global optimization of objective functions represented by ReLU networks. Mach. Learn. 112 (10) (2023)
Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett
Soy: An Efficient MILP Solver for Piecewise-Affine Systems. IROS (2023)
Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning. FMCAD (2023)
Runtian Zhou, Haoze Wu, Hammurabi Mendes, Jonad Pulaj
Verifying MILP Certificates with SMT Solvers. CoRR (2023)
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
Toward Certified Robustness Against Real-World Distribution Shifts. SaTML (2023)
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
Convex Bounds on the Softmax Function with Applications to Robustness Verification. AISTATS (2023)
Min Wu, Haoze Wu, Clark W. Barrett
VeriX: Towards Verified Explainability of Deep Neural Networks. NeurIPS (2023)
Haoze Wu, Clark W. Barrett, Nina Narodytska
Lemur: Integrating Large Language Models in Automated Program Verification. CoRR (2023)
Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett
Soy: An Efficient MILP Solver for Piecewise-Affine Systems. CoRR (2023)
Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu, Yedi Zhang, Clark W. Barrett
Towards Efficient Verification of Quantized Neural Networks. CoRR (2023)
Tom Zelazny, Haoze Wu, Clark W. Barrett, Guy Katz
On Optimizing Back-Substitution Methods for Neural Network Verification. FMCAD (2022)
Tom Zelazny, Haoze Wu, Clark W. Barrett, Guy Katz
On Optimizing Back-Substitution Methods for Neural Network Verification. CoRR (2022)
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
Toward Certified Robustness Against Real-World Distribution Shifts. CoRR (2022)
Haoze Wu, Clark W. Barrett, Mahmood Sharif, Nina Narodytska, Gagandeep Singh
Scalable Verification of GNN-based Job Schedulers. CoRR (2022)
Haoze Wu, Aleksandar Zeljic, Guy Katz, Clark W. Barrett
Efficient Neural Network Analysis with Sum-of-Infeasibilities. TACAS (1) (2022)
Haoze Wu, Aleksandar Zeljic, Guy Katz, Clark W. Barrett
Efficient Neural Network Analysis with Sum-of-Infeasibilities. CoRR (2022)
Min Wu, Haoze Wu, Clark W. Barrett
VeriX: Towards Verified Explainability of Deep Neural Networks. CoRR (2022)
Haoze Wu, Clark W. Barrett, Mahmood Sharif, Nina Narodytska, Gagandeep Singh
Scalable verification of GNN-based job schedulers. Proc. ACM Program. Lang. 6 (OOPSLA2) (2022)
Abhishek Nair, Saranyu Chattopadhyay, Haoze Wu, Alex Ozdemir, Clark W. Barrett
Proof-Stitch: Proof Combination for Divide and Conquer SAT Solvers. CoRR (2022)
Abhishek Nair, Saranyu Chattopadhyay, Haoze Wu, Alex Ozdemir, Clark W. Barrett
Proof-Stitch: Proof Combination for Divide-and-Conquer SAT Solvers. FMCAD (2022)
Alex Ozdemir, Haoze Wu, Clark W. Barrett
SAT Solving in the Serverless Cloud. FMCAD (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. CoRR (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. SAFECOMP (2021)
Guy Amir, Haoze Wu, Clark W. Barrett, Guy Katz
An SMT-Based Approach for Verifying Binarized Neural Networks. TACAS (2) (2021)
Guy Amir, Haoze Wu, Clark W. Barrett, Guy Katz
An SMT-Based Approach for Verifying Binarized Neural Networks. CoRR (2020)
Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer
Global Optimization of Objective Functions Represented by ReLU Networks. CoRR (2020)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. FMCAD (2020)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Ahmed Irfan, Kyle Julian, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. CoRR (2020)
Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
G2SAT: Learning to Generate SAT Formulas. CoRR (2019)
Guy Katz, Derek A. Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljic, David L. Dill, Mykel J. Kochenderfer, Clark W. Barrett
The Marabou Framework for Verification and Analysis of Deep Neural Networks. CAV (1) (2019)
Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
G2SAT: Learning to Generate SAT Formulas. NeurIPS (2019)
Haoze Wu, Raghuram Ramanujan
Learning to Generate Industrial SAT Instances. SOCS (2019)
Haoze Wu
Improving SAT-solving with Machine Learning. SIGCSE (2017)
Haoze Wu
Improve SAT-solving with Machine Learning. CoRR (2017)
Pei Huang, Yuting Yang, Haoze Wu, Ieva Daukantas, Min Wu, Fuqi Jia, Clark W. Barrett
Parallel Verification for δ-Equivalence of Neural Network Quantization. SAIV (2014)