| 2023 | CoRL | MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. | Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn |
| 2023 | ICML | Settling the Reward Hypothesis. | Michael Bowling, John D. Martin, David Abel, Will Dabney |
| 2020 | ICML | Stochastically Dominant Distributional Reinforcement Learning. | John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot |
| 2020 | IROS | Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs. | Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot |
| 2020 | IROS | Variational Filtering with Copula Models for SLAM. | John D. Martin, Kevin J. Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard |
| 2020 | IROS | Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction. | John McConnell, John D. Martin, Brendan J. Englot |
| 2018 | CoRL | Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation. | John D. Martin, Jinkun Wang, Brendan J. Englot |
| 2017 | CoRL | Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments. | John D. Martin, Brendan J. Englot |