| Pretraining Representations for Data-Efficient Reinforcement Learning M Schwarzer, N Rajkumar, M Noukhovitch, A Anand, L Charlin, D Hjelm, ... NeurIPS, 2021 | 92 | 2021 |
| In search of robust measures of generalization GK Dziugaite, A Drouin, B Neal, N Rajkumar, E Caballero, L Wang, ... NeurIPS, 2020 | 78 | 2020 |
| Evaluating the text-to-sql capabilities of large language models N Rajkumar, R Li, D Bahdanau arXiv preprint arXiv:2204.00498, 2022 | 49 | 2022 |
| Metadata archaeology: Unearthing data subsets by leveraging training dynamics SA Siddiqui, N Rajkumar, T Maharaj, D Krueger, S Hooker arXiv preprint arXiv:2209.10015, 2022 | 13 | 2022 |
| Harms from Increasingly Agentic Algorithmic Systems A Chan, R Salganik, A Markelius, C Pang, N Rajkumar, D Krasheninnikov, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 11 | 2023 |
| John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, and Tegan Maharaj. 2023. Harms from Increasingly Agentic … A Chan, R Salganik, A Markelius, C Pang, N Rajkumar, D Krasheninnikov, ... arXiv preprint arXiv:2302.10329, 0 | 8 | |
| Reclaiming the Digital Commons: A Public Data Trust for Training Data A Chan, H Bradley, N Rajkumar arXiv preprint arXiv:2303.09001, 2023 | 7 | 2023 |
| A New National Purpose: Innovation Can Power the Future of Britain J KAKKAD, B MACON-COONEY, J NORTHEND, J PHILLIPS, ... Tony Blair Institute for Global Change, 2023 | 2 | 2023 |
| Myriad: a real-world testbed to bridge trajectory optimization and deep learning N Howe, S Dufort-Labbé, N Rajkumar, PL Bacon Advances in Neural Information Processing Systems 35, 29801-29815, 2022 | 1 | 2022 |
| Self-supervision for data interpretability in image classification and sample efficiency in reinforcement learning N Rajkumar Université de Montréal, 2021 | | 2021 |
| RL: Generic reinforcement learning codebase in TensorFlow BM Li, A Cowen-Rivers, P Kozakowski, D Tao, SR Kamalakara, ... Journal of Open Source Software 4 (42), 1524, 2019 | | 2019 |
Laurent CharlinAssociate Professor, HEC Montréal & Mila, Canada CIFAR AI ChairVerified email at hec.ca
