| Reluplex: An efficient SMT solver for verifying deep neural networks G Katz, C Barrett, DL Dill, K Julian, MJ Kochenderfer Computer Aided Verification: 29th International Conference, CAV 2017 …, 2017 | 1939 | 2017 |
| Cooperative multi-agent control using deep reinforcement learning JK Gupta, M Egorov, M Kochenderfer Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers …, 2017 | 965 | 2017 |
| Decision making under uncertainty: theory and application MJ Kochenderfer MIT Press, 2015 | 712 | 2015 |
| Algorithms for Optimization MJ Kochenderfer, TA Wheeler MIT Press, 2019 | 549 | 2019 |
| The marabou framework for verification and analysis of deep neural networks G Katz, DA Huang, D Ibeling, K Julian, C Lazarus, R Lim, P Shah, ... Computer Aided Verification: 31st International Conference, CAV 2019, New …, 2019 | 484 | 2019 |
| Imitating driver behavior with generative adversarial networks A Kuefler, J Morton, T Wheeler, M Kochenderfer 2017 IEEE Intelligent Vehicles Symposium (IV), 204-211, 2017 | 455 | 2017 |
| Algorithms for verifying deep neural networks C Liu, T Arnon, C Lazarus, C Barrett, MJ Kochenderfer arXiv preprint arXiv:1903.06758, 2019 | 357 | 2019 |
| Policy compression for aircraft collision avoidance systems KD Julian, J Lopez, JS Brush, MP Owen, MJ Kochenderfer 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC), 1-10, 2016 | 278 | 2016 |
| Next generation airborne collision avoidance system MJ Kochenderfer, JE Holland, JP Chryssanthacopoulos Lincoln Laboratory Journal 19 (1), 17-33, 2012 | 259 | 2012 |
| Analysis of recurrent neural networks for probabilistic modeling of driver behavior J Morton, TA Wheeler, MJ Kochenderfer IEEE Transactions on Intelligent Transportation Systems 18 (5), 1289-1298, 2016 | 254 | 2016 |
| Combining planning and deep reinforcement learning in tactical decision making for autonomous driving CJ Hoel, K Driggs-Campbell, K Wolff, L Laine, MJ Kochenderfer IEEE transactions on intelligent vehicles 5 (2), 294-305, 2019 | 213 | 2019 |
| Online algorithms for POMDPs with continuous state, action, and observation spaces Z Sunberg, M Kochenderfer Proceedings of the International Conference on Automated Planning and …, 2018 | 206 | 2018 |
| Learning near optimal policies with low inherent bellman error A Zanette, A Lazaric, M Kochenderfer, E Brunskill International Conference on Machine Learning, 10978-10989, 2020 | 199 | 2020 |
| Generalizable intention prediction of human drivers at intersections DJ Phillips, TA Wheeler, MJ Kochenderfer 2017 IEEE intelligent vehicles symposium (IV), 1665-1670, 2017 | 197 | 2017 |
| Collision avoidance for unmanned aircraft using Markov decision processes S Temizer, M Kochenderfer, L Kaelbling, T Lozano-Pérez, J Kuchar AIAA guidance, navigation, and control conference, 8040, 2010 | 183 | 2010 |
| Adaptive stress testing for autonomous vehicles M Koren, S Alsaif, R Lee, MJ Kochenderfer 2018 IEEE Intelligent Vehicles Symposium (IV), 1-7, 2018 | 182 | 2018 |
| Deep neural network compression for aircraft collision avoidance systems KD Julian, MJ Kochenderfer, MP Owen Journal of Guidance, Control, and Dynamics 42 (3), 598-608, 2019 | 180 | 2019 |
| Airspace encounter models for estimating collision risk MJ Kochenderfer, MWM Edwards, LP Espindle, JK Kuchar, JD Griffith Journal of Guidance, Control, and Dynamics 33 (2), 487-499, 2010 | 167 | 2010 |
| Common sense data acquisition for indoor mobile robots R Gupta, MJ Kochenderfer AAAI, 605-610, 2004 | 165 | 2004 |
| Robust airborne collision avoidance through dynamic programming MJ Kochenderfer, JP Chryssanthacopoulos Massachusetts Institute of Technology, Lincoln Laboratory, Project Report, 2011 | 155 | 2011 |
Kyle David JulianReceived Ph.D. at Stanford UniversityVerified email at stanford.edu
