Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 3270 | 2023 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1211 | 2024 |
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 | 730* | 2021 |
Safe exploration in continuous action spaces G Dalal, K Dvijotham, M Vecerik, T Hester, C Paduraru, Y Tassa arXiv preprint arXiv:1801.08757, 2018 | 578 | 2018 |
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 | 222* | 2020 |
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 | 200 | 2023 |
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 | 175 | 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 | 103 | 2021 |
Training language models to self-correct via reinforcement learning A Kumar, V Zhuang, R Agarwal, Y Su, JD Co-Reyes, A Singh, K Baumli, ... arXiv preprint arXiv:2409.12917, 2024 | 59 | 2024 |
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 | 59 | 2022 |
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 | 53 | 2021 |
Transformers meet directed graphs S Geisler, Y Li, DJ Mankowitz, AT Cemgil, S Günnemann, C Paduraru International conference on machine learning, 11144-11172, 2023 | 43 | 2023 |
Off-policy evaluation in Markov decision processes C Paduraru McGill University, 2013 | 43 | 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 | 36 | 2022 |
Responding to new information in a mining complex: Fast mechanisms using machine learning C Paduraru, R Dimitrakopoulos Mining Technology, 2019 | 34 | 2019 |
Adaptive policies for short-term material flow optimization in a mining complex C Paduraru, R Dimitrakopoulos Mining Technology 127 (1), 56-63, 2018 | 29 | 2018 |
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 | 28 | 2021 |
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 | 28 | 2005 |
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 | 25 | 2019 |
Robust constrained reinforcement learning for continuous control with model misspecification DJ Mankowitz, DA Calian, R Jeong, C Paduraru, N Heess, S Dathathri, ... arXiv preprint arXiv:2010.10644, 2020 | 15 | 2020 |