| Maximum Entropy Inverse Reinforcement Learning BD Ziebart, AL Maas, JA Bagnell, AK Dey AAAI Conference on Artificial Intelligence, 1433-1438, 2008 | 3695 | 2008 |
| Activity forecasting KM Kitani, BD Ziebart, JA Bagnell, M Hebert European Conference on Computer Vision (ECCV), 201-214, 2012 | 951 | 2012 |
| Planning-based prediction for pedestrians BD Ziebart, N Ratliff, G Gallagher, C Mertz, K Peterson, JA Bagnell, ... International Conference on Intelligent Robots and Systems (IROS), 3931-3936, 2009 | 678 | 2009 |
| Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy BD Ziebart Carnegie Mellon University, 2010 | 663 | 2010 |
| Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior BD Ziebart, AL Maas, AK Dey, JA Bagnell International Conference on Ubiquitous Computing (Ubicomp), 322-331, 2008 | 401 | 2008 |
| Modeling interaction via the principle of maximum causal entropy BD Ziebart, JA Bagnell, AK Dey 🥈International Conference on Machine Learning (ICML), 1247-1254, 2010 | 373 | 2010 |
| System, method and device for predicting navigational decision-making behavior AK Dey, JA Bagnell, BD Ziebart US Patent 8,478,642, 2013 | 301 | 2013 |
| Robust classification under sample selection bias A Liu, B Ziebart 💡 Advances in Neural Information Processing Systems (NIPS), 37-45, 2014 | 157 | 2014 |
| Probabilistic pointing target prediction via inverse optimal control B Ziebart, A Dey, JA Bagnell 🥈International Conference on Intelligent User Interfaces (IUI), 1-10, 2012 | 116 | 2012 |
| Robust fairness under covariate shift A Rezaei, A Liu, O Memarrast, BD Ziebart Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9419-9427, 2021 | 96 | 2021 |
| Computational rationalization: The inverse equilibrium problem K Waugh, BD Ziebart, JA Bagnell 🏆 International Conference on Machine Learning., 2011 | 96 | 2011 |
| Robust covariate shift regression X Chen, M Monfort, A Liu, BD Ziebart Artificial Intelligence and Statistics, 1270-1279, 2016 | 95 | 2016 |
| TherML: occupancy prediction for thermostat control C Koehler, BD Ziebart, J Mankoff, AK Dey Pervasive and Ubiquitous Computing (Ubicomp), 103-112, 2013 | 92 | 2013 |
| Human Behavior Modeling with Maximum Entropy Inverse Optimal Control BD Ziebart, AL Maas, JA Bagnell, AK Dey AAAI Spring Symposium: Human Behavior Modeling, 92-, 2009 | 84 | 2009 |
| The principle of maximum causal entropy for estimating interacting processes BD Ziebart, JA Bagnell, AK Dey IEEE Transactions on Information Theory 59 (4), 1966-1980, 2013 | 83 | 2013 |
| Towards a pervasive computing benchmark A Ranganathan, J Al-Muhtadi, J Biehl, B Ziebart, RH Campbell, B Bailey Pervasive Computing and Communications Workshops, 194-198, 2005 | 80 | 2005 |
| Fairness for robust log loss classification A Rezaei, R Fathony, O Memarrast, B Ziebart Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5511-5518, 2020 | 75 | 2020 |
| Machine learning model to predict welding quality using air-coupled acoustic emission and weld inputs K Asif, L Zhang, S Derrible, JE Indacochea, D Ozevin, B Ziebart Journal of Intelligent Manufacturing, 1-15, 2022 | 69 | 2022 |
| Both nearest neighbours and long-term affiliates predict individual locations during collective movement in wild baboons DR Farine, A Strandburg-Peshkin, T Berger-Wolf, B Ziebart, I Brugere, J Li, ... Scientific reports 6 (1), 27704, 2016 | 69 | 2016 |
| Feedback in imitation learning: The three regimes of covariate shift J Spencer, S Choudhury, A Venkatraman, B Ziebart, JA Bagnell arXiv preprint arXiv:2102.02872, 2021 | 68 | 2021 |
J. Andrew BagnellCarnegie Mellon UniversityVerified email at ri.cmu.edu
