John D. Martin

According to our database, John D. Martin authored at least 14 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment.

Xi Lin, Paul Szenher, John D. Martin, Brendan J. Englot

CoRR, 2023

Settling the Reward Hypothesis.

Michael Bowling, John D. Martin, David Abel, Will Dabney

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the Conference on Robot Learning, 2023

2022

Should Models Be Accurate?

Esra'a Saleh, John D. Martin, Anna Koop, Arash Pourzarabi, Michael Bowling

CoRR, 2022

2021

Modeling the onset of symptoms of COVID-19: Effects of SARS-CoV-2 variant.

Joseph R. Larsen, Margaret R. Martin, John D. Martin, James B. Hicks, Peter Kuhn

PLoS Comput. Biol., 2021

Adapting the Function Approximation Architecture in Online Reinforcement Learning.

John D. Martin, Joseph Modayil

CoRR, 2021

2020

On Catastrophic Interference in Atari 2600 Games.

William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle

CoRR, 2020

Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction.

John McConnell, John D. Martin, Brendan J. Englot

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Variational Filtering with Copula Models for SLAM.

John D. Martin, Kevin J. Doherty, Caralyn Cyr, Brendan J. Englot, John J. Leonard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs.

Fanfei Chen, John D. Martin, Yewei Huang, Jinkun Wang, Brendan J. Englot

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Stochastically Dominant Distributional Reinforcement Learning.

John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Recursive Sparse Pseudo-input Gaussian Process SARSA.

John D. Martin, Brendan J. Englot

CoRR, 2018

Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation.

John D. Martin, Jinkun Wang, Brendan J. Englot

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments.

John D. Martin, Brendan J. Englot

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017