| Iterative Reachability Estimation for Safe Reinforcement Learning M Ganai, Z Gong, C Yu, S Herbert, S Gao Neural Information Processing Systems (NeurIPS), 2023 | 13 | 2023 |
| Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates U Mandal, G Amir, H Wu, I Daukantas, FL Newell, UJ Ravaioli, B Meng, ... Formal Methods in Computer-Aided Design (FMCAD), 2024 | 5 | 2024 |
| Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models M Ganai, C Hirayama, YC Chang, S Gao IEEE International Conference on Robotics and Automation (ICRA), 2913 - 2920, 2023 | 5 | 2023 |
| Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey M Ganai, S Gao, S Herbert IEEE Open Journal of Control Systems (OJ-CSYS) 3, 310-324, 2024 | 2 | 2024 |
| Safe and Reliable Training of Learning-Based Aerospace Controllers U Mandal, G Amir, H Wu, I Daukantas, FL Newell, U Ravaioli, B Meng, ... Digital Avionics Systems Conference (DASC), 2024 | 1 | 2024 |
| Hamilton-Jacobi Reachability Estimation in Reinforcement Learning M Ganai University of California, San Diego, 2024 | | 2024 |
| Target-independent XLA optimization using Reinforcement Learning M Ganai, H Li, T Enns, Y Wang, R Huang Workshop on ML for Systems at NeurIPS, 2022 | | 2022 |
| Identifying Merged Tracks in Dense Environments with Machine Learning P McCormack, M Ganai, B Nachman, M Garcia-Sciveres Connecting the Dots and Workshop on Intelligent Trackers (CTD/WIT), 2019 | | 2019 |
