| Data-driven chance constrained control using kernel distribution embeddings A Thorpe, T Lew, M Oishi, M Pavone Learning for Dynamics and Control Conference, 790-802, 2022 | 20 | 2022 |
| State-Based Confidence Bounds for Data-Driven Stochastic Reachability Using Hilbert Space Embeddings AJ Thorpe, KR Ortiz, MMK Oishi Automatica, 2022 | 13* | 2022 |
| Learning approximate forward reachable sets using separating kernels AJ Thorpe, KR Ortiz, MMK Oishi Learning for dynamics and control, 201-212, 2021 | 12 | 2021 |
| Model-Free Stochastic Reachability Using Kernel Distribution Embeddings AJ Thorpe, MMK Oishi IEEE Control Systems Letters, 2019 | 11 | 2019 |
| Arch-comp21 category report: Stochastic models A Abate, H Blom, M Bouissou, N Cauchi, H Chraibi, J Delicaris, ... 8th International Workshop on Applied Verification of Continuous and Hybrid …, 2021 | 10 | 2021 |
| Physics-informed kernel embeddings: Integrating prior system knowledge with data-driven control AJ Thorpe, C Neary, F Djeumou, MMK Oishi, U Topcu arXiv preprint arXiv:2301.03565, 2023 | 9 | 2023 |
| Stochastic optimal control via Hilbert space embeddings of distributions AJ Thorpe, MMK Oishi 2021 60th IEEE Conference on Decision and Control (CDC), 904-911, 2021 | 9 | 2021 |
| SOCKS: A stochastic optimal control and reachability toolbox using kernel methods A Thorpe, M Oishi Proceedings of the 25th ACM International Conference on Hybrid Systems …, 2022 | 7 | 2022 |
| SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions AJ Thorpe, KR Ortiz, MMK Oishi 2021 60th IEEE Conference on Decision and Control (CDC), 5073-5079, 2021 | 5 | 2021 |
| Approximate Stochastic Reachability for High Dimensional Systems AJ Thorpe, V Sivaramakrishnan, MMK Oishi arXiv preprint arXiv:1910.10818, 2019 | 5 | 2019 |
| Sensor selection for dynamics-driven user-interface design AP Vinod, AJ Thorpe, PA Olaniyi, TH Summers, MMK Oishi IEEE Transactions on Control Systems Technology 30 (1), 71-84, 2021 | 4 | 2021 |
| Data-driven stochastic optimal control using kernel gradients AJ Thorpe, JA Gonzales, MMK Oishi 2023 American Control Conference (ACC), 2548-2553, 2023 | 3 | 2023 |
| Characterizing Within-Driver Variability in Driving Dynamics During Obstacle Avoidance Maneuvers KR Ortiz, AJ Thorpe, AM Perez, M Luster, BJ Pitts, M Oishi IFAC-PapersOnLine 55 (41), 13-19, 2022 | 3 | 2022 |
| Autonomous Multi-Platform Sensor Scheduling for Intelligence Surveillance and Reconnaissance. J Richards, A Patel, A Thorpe, R Schlossman Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | 2 | 2019 |
| GPSINDy: Data-Driven Discovery of Equations of Motion J Hsin, S Agarwal, A Thorpe, D Fridovich-Keil arXiv preprint arXiv:2309.11076, 2023 | 1 | 2023 |
| Trust-based user-interface design for human-automation systems AP Vinod, AJ Thorpe, PA Olaniyi, TH Summers, MMK Oishi arXiv preprint arXiv:2004.07176, 2020 | 1 | 2020 |
| Phononic Barrier Communication: Channeling Information and Energy through Metallic Barriers with High Fidelity High efficiency and Low Bit Errors. IF El-Kady, CM Reinke, JR Pillars, CL Arrington, A Thorpe Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | 1 | 2019 |
| Act Natural! Projecting Autonomous System Trajectories Into Naturalistic Behavior Sets HI Khan, AJ Thorpe, D Fridovich-Keil arXiv preprint arXiv:2405.19292, 2024 | | 2024 |
| Zero-Shot Transfer of Neural ODEs T Ingebrand, AJ Thorpe, U Topcu arXiv preprint arXiv:2405.08954, 2024 | | 2024 |
| Sensing Resource Allocation Against Data-Poisoning Attacks in Traffic Routing Y Yu, AJ Thorpe, J Milzman, D Fridovich-Keil, U Topcu arXiv preprint arXiv:2404.02876, 2024 | | 2024 |
Meeko OishiProfessor, Electrical and Computer Engineering, University of New Mexico在 unm.edu 的电子邮件经过验证
