| 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 | 740 | 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 | 650 | 2020 |
| 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 | 435 | 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 | 353 | 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 | 346 | 2012 |
| Dopamine: A research framework for deep reinforcement learning PS Castro, S Moitra, C Gelada, S Kumar, MG Bellemare arXiv preprint arXiv:1812.06110, 2018 | 311 | 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 | 226 | 2013 |
| Contrastive behavioral similarity embeddings for generalization in reinforcement learning R Agarwal, MC Machado, PS Castro, MG Bellemare arXiv preprint arXiv:2101.05265, 2021 | 212 | 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 | 198 | 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 | 187 | 2024 |
| 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 | 152 | 2020 |
| Revisiting rainbow: Promoting more insightful and inclusive deep reinforcement learning research JSO Ceron, PS Castro International Conference on Machine Learning, 1373-1383, 2021 | 145* | 2021 |
| 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 | 141 | 2011 |
| 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 | 109 | 2019 |
| 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 | 104 | 2019 |
| Methods for computing state similarity in Markov decision processes N Ferns, PS Castro, D Precup, P Panangaden arXiv preprint arXiv:1206.6836, 2012 | 101 | 2012 |
| The dormant neuron phenomenon in deep reinforcement learning G Sokar, R Agarwal, PS Castro, U Evci International Conference on Machine Learning, 32145-32168, 2023 | 90 | 2023 |
| Bigger, better, faster: Human-level atari with human-level efficiency M Schwarzer, JSO Ceron, A Courville, MG Bellemare, R Agarwal, ... International Conference on Machine Learning, 30365-30380, 2023 | 86 | 2023 |
| 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 | 82* | 2022 |
| Using bisimulation for policy transfer in MDPs P Castro, D Precup Proceedings of the AAAI conference on artificial intelligence 24 (1), 1065-1070, 2010 | 76 | 2010 |
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