| Safe exploration in continuous action spaces G Dalal, K Dvijotham, M Vecerik, T Hester, C Paduraru, Y Tassa arXiv preprint arXiv:1801.08757, 2018 | 381 | 2018 |
| Challenges of real-world reinforcement learning: definitions, benchmarks and analysis G Dulac-Arnold, N Levine, DJ Mankowitz, J Li, C Paduraru, S Gowal, ... Machine Learning 110 (9), 2419-2468, 2021 | 330* | 2021 |
| Rl unplugged: A suite of benchmarks for offline reinforcement learning C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ... Advances in Neural Information Processing Systems 33, 7248-7259, 2020 | 142* | 2020 |
| Hyperparameter selection for offline reinforcement learning TL Paine, C Paduraru, A Michi, C Gulcehre, K Zolna, A Novikov, Z Wang, ... arXiv preprint arXiv:2007.09055, 2020 | 117 | 2020 |
| Benchmarks for deep off-policy evaluation J Fu, M Norouzi, O Nachum, G Tucker, Z Wang, A Novikov, M Yang, ... arXiv preprint arXiv:2103.16596, 2021 | 53 | 2021 |
| Autoregressive dynamics models for offline policy evaluation and optimization MR Zhang, TL Paine, O Nachum, C Paduraru, G Tucker, Z Wang, ... arXiv preprint arXiv:2104.13877, 2021 | 31 | 2021 |
| Off-policy evaluation in Markov decision processes C Paduraru McGill University, 2013 | 30 | 2013 |
| Off-policy learning with options and recognizers D Precup, C Paduraru, A Koop, RS Sutton, S Singh Advances in Neural Information Processing Systems 18, 2005 | 27 | 2005 |
| Responding to new information in a mining complex: Fast mechanisms using machine learning C Paduraru, R Dimitrakopoulos Mining Technology, 2019 | 24 | 2019 |
| Adaptive policies for short-term material flow optimization in a mining complex C Paduraru, R Dimitrakopoulos Mining Technology 127 (1), 56-63, 2018 | 20 | 2018 |
| Faster sorting algorithms discovered using deep reinforcement learning DJ Mankowitz, A Michi, A Zhernov, M Gelmi, M Selvi, C Paduraru, ... Nature 618 (7964), 257-263, 2023 | 16 | 2023 |
| Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm H Kalesse, T Vogl, C Paduraru, E Luke Atmospheric Measurement Techniques 12 (8), 4591-4617, 2019 | 15 | 2019 |
| Active offline policy selection K Konyushova, Y Chen, T Paine, C Gulcehre, C Paduraru, DJ Mankowitz, ... Advances in Neural Information Processing Systems 34, 24631-24644, 2021 | 14 | 2021 |
| Grounding Abstractions in Predictive State Representations. B Tanner, V Bulitko, A Koop, C Paduraru IJCAI, 1077-1082, 2007 | 14 | 2007 |
| Coptidice: Offline constrained reinforcement learning via stationary distribution correction estimation J Lee, C Paduraru, DJ Mankowitz, N Heess, D Precup, KE Kim, A Guez arXiv preprint arXiv:2204.08957, 2022 | 13 | 2022 |
| An empirical analysis of off-policy learning in discrete mdps C Păduraru, D Precup, J Pineau, G Comănici European Workshop on Reinforcement Learning, 89-102, 2013 | 10 | 2013 |
| Controlling commercial cooling systems using reinforcement learning J Luo, C Paduraru, O Voicu, Y Chervonyi, S Munns, J Li, C Qian, P Dutta, ... arXiv preprint arXiv:2211.07357, 2022 | 8 | 2022 |
| Planning with approximate and learned models of markov decision processes C Păduraru | 8 | 2007 |
| A framework for computing bounds for the return of a policy C Păduraru, D Precup, J Pineau European Workshop on Reinforcement Learning, 201-212, 2011 | 7 | 2011 |
| Model-based reinforcement learning with state aggregation C Paduraru, R Kaplow, D Precup, J Pineau 8th European Workshop on Reinforcement Learning, 2008 | 7 | 2008 |
