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2020 – today
- 2024
[i13]Rafael Rafailov, Kyle Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRR abs/2401.03306 (2024)- [i12]Bradley Burega, John D. Martin, Luke Kapeluck, Michael Bowling:
Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning. CoRR abs/2406.19561 (2024) - 2023
- [c8]Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn:
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. CoRL 2023: 3654-3671 - [c7]Michael Bowling, John D. Martin, David Abel, Will Dabney:
Settling the Reward Hypothesis. ICML 2023: 3003-3020 - [i11]Xi Lin, Paul Szenher, John D. Martin, Brendan J. Englot:
Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment. CoRR abs/2304.09996 (2023) - 2022
- [i10]Esra'a Saleh, John D. Martin, Anna Koop, Arash Pourzarabi, Michael Bowling:
Should Models Be Accurate? CoRR abs/2205.10736 (2022) - [i9]Michael Bowling, John D. Martin, David Abel, Will Dabney:
Settling the Reward Hypothesis. CoRR abs/2212.10420 (2022) - 2021
- [j1]Joseph R. Larsen
, Margaret R. Martin, John D. Martin, James B. Hicks, Peter Kuhn:
Modeling the onset of symptoms of COVID-19: Effects of SARS-CoV-2 variant. PLoS Comput. Biol. 17(12) (2021) - [i8]John D. Martin, Joseph Modayil:
Adapting the Function Approximation Architecture in Online Reinforcement Learning. CoRR abs/2106.09776 (2021) - 2020
- [c6]John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot:
Stochastically Dominant Distributional Reinforcement Learning. ICML 2020: 6745-6754 - [c5]John McConnell, John D. Martin, Brendan J. Englot:
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction. IROS 2020: 1653-1660 - [c4]John D. Martin, Kevin J. Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard:
Variational Filtering with Copula Models for SLAM. IROS 2020: 5066-5073 - [c3]Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot:
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs. IROS 2020: 6140-6147 - [i7]William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle:
On Catastrophic Interference in Atari 2600 Games. CoRR abs/2002.12499 (2020) - [i6]John McConnell, John D. Martin, Brendan J. Englot:
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction. CoRR abs/2007.10407 (2020) - [i5]Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot:
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs. CoRR abs/2007.12640 (2020) - [i4]John D. Martin, Kevin J. Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard:
Variational Filtering with Copula Models for SLAM. CoRR abs/2008.00504 (2020)
2010 – 2019
- 2019
- [i3]John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot:
Stochastically Dominant Distributional Reinforcement Learning. CoRR abs/1905.07318 (2019) - 2018
- [c2]John D. Martin, Jinkun Wang, Brendan J. Englot:
Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation. CoRL 2018: 179-189 - [i2]John D. Martin, Jinkun Wang, Brendan J. Englot:
Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation. CoRR abs/1810.01217 (2018) - [i1]John D. Martin, Brendan J. Englot:
Recursive Sparse Pseudo-input Gaussian Process SARSA. CoRR abs/1811.07201 (2018) - 2017
- [c1]John D. Martin, Brendan J. Englot:
Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments. CoRL 2017: 438-447
Coauthor Index
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