David Scott Krueger

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Tegan MaharajAssistant Professor at University of TorontoVerified email at polymtl.ca
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Nicolas BallasMeta AI ResearchVerified email at meta.com
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchVerified email at servicenow.com
Stanisław JastrzębskiChief Technology Officer & Chief Scientist @ Molecule.OneVerified email at molecule.one
Devansh ArpitRashi.aiVerified email at rashi.ai
Asja FischerProfessor for Machine Learning, Ruhr University BochumVerified email at ini.rub.de
Maxinder S. KanwalPhD Student, Stanford UniversityVerified email at stanford.edu
Emmanuel BengioMcGill UniversityVerified email at mail.mcgill.ca
Jan LeikeOpenAIVerified email at openai.com
Laurent DinhAppleVerified email at apple.com
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaVerified email at iro.umontreal.ca
Ethan CaballeroMila (Montreal Institute for Learning Algorithms)Verified email at mila.quebec
Chin-Wei HuangMicrosoft ResearchVerified email at microsoft.com
Jörn-Henrik JacobsenApple AI/ML ResearchVerified email at vectorinstitute.ai
Amy ZhangAssistant Professor of Electrical and Computer Engineering at University of Texas at AustinVerified email at austin.utexas.edu
Jonathan BinasVivid MachinesVerified email at iro.umontreal.ca
Rémi Le PriolPhD from MILA, University of MontréalVerified email at umontreal.ca
Dmitrii KrasheninnikovUniversity of CambridgeVerified email at cam.ac.uk

David Scott Krueger

University Assistant Professor, University of Cambridge

Verified email at cam.ac.uk - Homepage

AI Alignment Deep Learning


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Nice: Non-linear independent components estimation L Dinh, D Krueger, Y Bengio arXiv preprint arXiv:1410.8516, 2014	2003	2014
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	1655*	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	619	2021
Neural autoregressive flows CW Huang, D Krueger, A Lacoste, A Courville International Conference on Machine Learning (ICML) 2018, 2018	459	2018
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, 2016	369	2016
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	286	2020
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	201	2018
Bayesian hypernetworks D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville arXiv preprint arXiv:1710.04759, 2017	146	2017
Zero-bias autoencoders and the benefits of co-adapting features K Konda, R Memisevic, D Krueger International Conference on Learning Representations (ICLR) 2015, 2014	109*	2014
Regularizing rnns by stabilizing activations D Krueger, R Memisevic International Conference on Learning Representations (ICLR) 2016, 2015	80	2015
Nested lstms JRA Moniz, D Krueger Asian Conference on Machine Learning, 530-544, 2017	79	2017
Defining and characterizing reward gaming J Skalse, N Howe, D Krasheninnikov, D Krueger Advances in Neural Information Processing Systems 35, 9460-9471, 2022	47	2022
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, ... arXiv preprint arXiv:2307.15217, 2023	45	2023
Hidden Incentives for Auto-Induced Distributional Shift D Krueger, T Maharaj, J Leike arXiv preprint arXiv:2009.09153, 2020	45*	2020
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	42	2022
AI research considerations for human existential safety (ARCHES) A Critch, D Krueger arXiv preprint arXiv:2006.04948, 2020	39	2020
Deep prior A Lacoste, T Boquet, N Rostamzadeh, B Oreshkin, W Chung, D Krueger arXiv preprint arXiv:1712.05016, 2017	33*	2017
Active reinforcement learning: Observing rewards at a cost D Krueger, J Leike, O Evans, J Salvatier arXiv preprint arXiv:2011.06709, 2016	29	2016
Filling gaps in trustworthy development of AI S Avin, H Belfield, M Brundage, G Krueger, J Wang, A Weller, ... Science 374 (6573), 1327-1329, 2021	23	2021
Broken neural scaling laws E Caballero, K Gupta, I Rish, D Krueger arXiv preprint arXiv:2210.14891, 2022	18	2022

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