| Optimization and abstraction: a synergistic approach for analyzing neural network robustness G Anderson, S Pailoor, I Dillig, S Chaudhuri Proceedings of the 40th ACM SIGPLAN conference on programming language …, 2019 | 106 | 2019 |
| Neurosymbolic reinforcement learning with formally verified exploration G Anderson, A Verma, I Dillig, S Chaudhuri Advances in neural information processing systems 33, 6172-6183, 2020 | 72 | 2020 |
| Learning abstractions for program synthesis X Wang, G Anderson, I Dillig, KL McMillan Computer Aided Verification: 30th International Conference, CAV 2018, Held …, 2018 | 14 | 2018 |
| Guiding safe exploration with weakest preconditions G Anderson, S Chaudhuri, I Dillig arXiv preprint arXiv:2209.14148, 2022 | 2 | 2022 |
| Certifiably Robust Reinforcement Learning through Model-Based Abstract Interpretation C Yang, G Anderson, S Chaudhuri 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 233-251, 2024 | | 2024 |
| Neurosymbolic approaches to safe machine learning G Anderson | | 2023 |
| Policy Optimization with Robustness Certificates. C Yang, G Anderson, S Chaudhuri CoRR, 2023 | | 2023 |
| 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)| 979-8-3503-4950-4/24/$31.00© 2024 IEEE| DOI: 10.1109/SaTML59370. 2024.00043 U Aïvodji, G Anderson, R Anderson, S Aydore, A Azize, D Basu, ... | | |
