John D. Martin

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 22

Top Topics

Reinforcement Learning

Top Venues

Publications

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 (2024)
Bradley Burega, John D. Martin, Luke Kapeluck, Michael Bowling
Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning. CoRR (2024)
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)
Xi Lin, Paul Szenher, John D. Martin, Brendan J. Englot
Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment. CoRR (2023)
Michael Bowling, John D. Martin, David Abel, Will Dabney
Settling the Reward Hypothesis. ICML (2023)
Esra'a Saleh, John D. Martin, Anna Koop, Arash Pourzarabi, Michael Bowling
Should Models Be Accurate? CoRR (2022)
Michael Bowling, John D. Martin, David Abel, Will Dabney
Settling the Reward Hypothesis. CoRR (2022)
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)
John D. Martin, Joseph Modayil
Adapting the Function Approximation Architecture in Online Reinforcement Learning. CoRR (2021)
William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
On Catastrophic Interference in Atari 2600 Games. CoRR (2020)
John D. Martin, Kevin Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard
Variational Filtering with Copula Models for SLAM. IROS (2020)
John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot
Stochastically Dominant Distributional Reinforcement Learning. ICML (2020)
John D. Martin, Kevin Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard
Variational Filtering with Copula Models for SLAM. CoRR (2020)
Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs. IROS (2020)
John McConnell, John D. Martin, Brendan J. Englot
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction. CoRR (2020)
John McConnell, John D. Martin, Brendan J. Englot
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction. IROS (2020)
Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs. CoRR (2020)
John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot
Stochastically Dominant Distributional Reinforcement Learning. CoRR (2019)
John D. Martin, Brendan J. Englot
Recursive Sparse Pseudo-input Gaussian Process SARSA. CoRR (2018)
John D. Martin, Jinkun Wang, Brendan J. Englot
Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation. CoRR (2018)
John D. Martin, Jinkun Wang, Brendan J. Englot
Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation. CoRL (2018)
John D. Martin, Brendan J. Englot
Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments. CoRL (2017)