| Autonomous exploration under uncertainty via deep reinforcement learning on graphs F Chen, JD Martin, Y Huang, J Wang, B Englot 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 76 | 2020 |
| Settling the reward hypothesis M Bowling, JD Martin, D Abel, W Dabney International Conference on Machine Learning, 3003-3020, 2023 | 37 | 2023 |
| Fusing concurrent orthogonal wide-aperture sonar images for dense underwater 3d reconstruction J McConnell, JD Martin, B Englot 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 30 | 2020 |
| Stochastically dominant distributional reinforcement learning J Martin, M Lyskawinski, X Li, B Englot International conference on machine learning, 6745-6754, 2020 | 26 | 2020 |
| On catastrophic interference in atari 2600 games W Fedus, D Ghosh, JD Martin, MG Bellemare, Y Bengio, H Larochelle arXiv preprint arXiv:2002.12499, 2020 | 18 | 2020 |
| Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation J Martin, J Wang, B Englot Conference on Robot Learning (CoRL) 87, 2018 | 17 | 2018 |
| Moto: Offline pre-training to online fine-tuning for model-based robot learning R Rafailov, KB Hatch, V Kolev, JD Martin, M Phielipp, C Finn Conference on Robot Learning, 3654-3671, 2023 | 8 | 2023 |
| Variational filtering with copula models for SLAM JD Martin, K Doherty, C Cyr, B Englot, J Leonard 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 5 | 2020 |
| Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments J Martin, B Englot Conference on Robot Learning (CoRL) 78, 2017 | 5 | 2017 |
| Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment X Lin, P Szenher, JD Martin, B Englot 2023 20th International Conference on Ubiquitous Robots (UR), 287-294, 2023 | 2 | 2023 |
| Should models be accurate? E Saleh, JD Martin, A Koop, A Pourzarabi, M Bowling arXiv preprint arXiv:2205.10736, 2022 | 2 | 2022 |
| Learning to prioritize planning updates in model-based reinforcement learning B Burega, JD Martin, M Bowling Sixth Workshop on Meta-Learning at the Conference on Neural Information …, 2022 | 2 | 2022 |
| Adapting the Function Approximation Architecture in Online Reinforcement Learning JD Martin, J Modayil arXiv preprint arXiv:2106.09776, 2021 | 2 | 2021 |
| MOTO: Offline to Online Fine-tuning for Model-Based Reinforcement Learning R Rafailov, KB Hatch, V Kolev, JD Martin, M Phielipp, C Finn Workshop on Reincarnating Reinforcement Learning at ICLR 2023, 0 | 1 | |
| Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning B Burega, JD Martin, L Kapeluck, M Bowling arXiv preprint arXiv:2406.19561, 2024 | | 2024 |
| Time to Take Embodiment Seriously JD Martin RL as a Model of Agency Workshop, Reinforcement Learning and Decision Making …, 2022 | | 2022 |
| Model-Based Adversarial Imitation Learning As Online Fine-Tuning R Rafailov, V Kolev, KB Hatch, JD Martin, M Phielipp, J Wu, C Finn Workshop on Reincarnating Reinforcement Learning at ICLR 2023, 0 | | |
| The Stochastic Road Network Environment for Robust Reinforcement Learning JD Martin, P Szenher, X Lin, B Englot | | |
Brendan EnglotProfessor, Stevens Institute of TechnologyVerified email at stevens.edu
