Deep reinforcement learning at the edge of the statistical precipice R Agarwal, M Schwarzer, PS Castro, AC Courville, M Bellemare Advances in neural information processing systems 34, 29304-29320, 2021 | 497 | 2021 |
Rigging the lottery: Making all tickets winners U Evci, T Gale, J Menick, PS Castro, E Elsen International conference on machine learning, 2943-2952, 2020 | 489 | 2020 |
From taxi GPS traces to social and community dynamics: A survey PS Castro, D Zhang, C Chen, S Li, G Pan ACM Computing Surveys (CSUR) 46 (2), 1-34, 2013 | 338 | 2013 |
Urban traffic modelling and prediction using large scale taxi GPS traces PS Castro, D Zhang, S Li International Conference on Pervasive Computing, 57-72, 2012 | 336 | 2012 |
Autonomous navigation of stratospheric balloons using reinforcement learning MG Bellemare, S Candido, PS Castro, J Gong, MC Machado, S Moitra, ... Nature 588 (7836), 77-82, 2020 | 329 | 2020 |
Dopamine: A research framework for deep reinforcement learning PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare arXiv preprint arXiv:1812.06110, 2018 | 282 | 2018 |
iBOAT: Isolation-based online anomalous trajectory detection C Chen, D Zhang, PS Castro, N Li, L Sun, S Li, Z Wang IEEE Transactions on Intelligent Transportation Systems 14 (2), 806-818, 2013 | 212 | 2013 |
Contrastive behavioral similarity embeddings for generalization in reinforcement learning R Agarwal, MC Machado, PS Castro, MG Bellemare arXiv preprint arXiv:2101.05265, 2021 | 180 | 2021 |
TF-Agents: A library for reinforcement learning in tensorflow S Guadarrama, A Korattikara, O Ramirez, P Castro, E Holly, S Fishman, ... GitHub repository, 2018 | 166 | 2018 |
Real-time detection of anomalous taxi trajectories from GPS traces C Chen, D Zhang, P Samuel Castro, N Li, L Sun, S Li International Conference on Mobile and Ubiquitous Systems: Computing …, 2011 | 138 | 2011 |
Scalable methods for computing state similarity in deterministic markov decision processes PS Castro Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10069 …, 2020 | 125 | 2020 |
Revisiting rainbow: Promoting more insightful and inclusive deep reinforcement learning research JSO Ceron, PS Castro International Conference on Machine Learning, 1373-1383, 2021 | 111* | 2021 |
A geometric perspective on optimal representations for reinforcement learning M Bellemare, W Dabney, R Dadashi, A Ali Taiga, PS Castro, N Le Roux, ... Advances in neural information processing systems 32, 2019 | 95 | 2019 |
Methods for computing state similarity in Markov decision processes N Ferns, PS Castro, D Precup, P Panangaden arXiv preprint arXiv:1206.6836, 2012 | 95 | 2012 |
A comparative analysis of expected and distributional reinforcement learning C Lyle, MG Bellemare, PS Castro Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4504-4511, 2019 | 85 | 2019 |
Using bisimulation for policy transfer in MDPs P Castro, D Precup Proceedings of the AAAI conference on artificial intelligence 24 (1), 1065-1070, 2010 | 64 | 2010 |
An atari model zoo for analyzing, visualizing, and comparing deep reinforcement learning agents FP Such, V Madhavan, R Liu, R Wang, PS Castro, Y Li, J Zhi, L Schubert, ... arXiv preprint arXiv:1812.07069, 2018 | 60 | 2018 |
Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks M Chevalier-Boisvert, B Dai, M Towers, R Perez-Vicente, L Willems, ... Advances in Neural Information Processing Systems 36, 2024 | 54 | 2024 |
Real time anomalous trajectory detection and analysis L Sun, D Zhang, C Chen, PS Castro, S Li, Z Wang Mobile Networks and Applications 18, 341-356, 2013 | 48 | 2013 |
Reincarnating reinforcement learning: Reusing prior computation to accelerate progress R Agarwal, M Schwarzer, PS Castro, AC Courville, M Bellemare Advances in Neural Information Processing Systems 35, 28955-28971, 2022 | 46* | 2022 |