| Nice: Non-linear independent components estimation L Dinh, D Krueger, Y Bengio Workshop at ICLR, 2015, 2015 | 3099 | 2015 |
| A closer look at memorization in deep networks D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ... International Conference on Machine Learning (ICML) 2017, 2017 | 2554* | 2017 |
| Out-of-distribution generalization via risk extrapolation (rex) D Krueger, E Caballero, JH Jacobsen, A Zhang, J Binas, D Zhang, ... International conference on machine learning, 5815-5826, 2021 | 1261 | 2021 |
| Open problems and fundamental limitations of reinforcement learning from human feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... Transactions on Machine Learning Research, 2023 | 774 | 2023 |
| Toward trustworthy AI development: mechanisms for supporting verifiable claims M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ... arXiv preprint arXiv:2004.07213, 2020 | 638 | 2020 |
| Neural autoregressive flows CW Huang, D Krueger, A Lacoste, A Courville International Conference on Machine Learning (ICML) 2018, 2018 | 634 | 2018 |
| Managing extreme AI risks amid rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, T Darrell, YN Harari, ... Science 384 (6698), 842-845, 2024 | 549* | 2024 |
| Scalable agent alignment via reward modeling: a research direction J Leike, D Krueger, T Everitt, M Martic, V Maini, S Legg arXiv preprint arXiv:1811.07871, 2018 | 532 | 2018 |
| Defining and characterizing reward gaming J Skalse, N Howe, D Krasheninnikov, D Krueger Advances in Neural Information Processing Systems 35, 9460-9471, 2022 | 423 | 2022 |
| Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... International Conference on Learning Representations (ICLR) 2017, 2017 | 410 | 2017 |
| Foundational challenges in assuring alignment and safety of large language models U Anwar, A Saparov, J Rando, D Paleka, M Turpin, P Hase, ES Lubana, ... Transactions on Machine Learning Research, 2024 | 252 | 2024 |
| Bayesian hypernetworks D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville Workshop on Bayesian Deep Learning at NeurIPS, 2017, 2017 | 213 | 2017 |
| 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 | 182 | 2023 |
| Goal misgeneralization in deep reinforcement learning LL Di Langosco, J Koch, LD Sharkey, J Pfau, D Krueger International Conference on Machine Learning, 12004-12019, 2022 | 176 | 2022 |
| Reward model ensembles help mitigate overoptimization T Coste, U Anwar, R Kirk, D Krueger International Conference on Learning Representations, 2024, 2024 | 154 | 2024 |
| Black-box access is insufficient for rigorous ai audits S Casper, C Ezell, C Siegmann, N Kolt, TL Curtis, B Bucknall, A Haupt, ... Proceedings of the 2024 ACM Conference on Fairness, Accountability, and …, 2024 | 151 | 2024 |
| Characterizing manipulation from AI systems M Carroll, A Chan, H Ashton, D Krueger Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms …, 2023 | 123 | 2023 |
| Broken neural scaling laws E Caballero, K Gupta, I Rish, D Krueger International Conference on Learning Representations, 2023, 2023 | 117 | 2023 |
| Zero-bias autoencoders and the benefits of co-adapting features K Konda, R Memisevic, D Krueger International Conference on Learning Representations (ICLR) 2015, 2015 | 117* | 2015 |
| Nested lstms JRA Moniz, D Krueger Asian Conference on Machine Learning, 530-544, 2017 | 99 | 2017 |
Tegan MaharajAssistant Professor at MilaVerified email at polymtl.ca
