Tegan Maharaj

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David Scott KruegerUniversity Assistant Professor, University of CambridgeVerified email at cam.ac.uk
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Chris PalProfessor, Polytechnique Montréal & Mila, ServiceNow Research, Canada CIFAR AI ChairVerified email at polymtl.ca
Nicolas BallasMeta AI ResearchVerified email at meta.com
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
Lynn H. KaackHertie SchoolVerified email at hertie-school.org
Natasha JaquesUniversity of Washington, Google ResearchVerified email at google.com
Sasha LuccioniHugging FaceVerified email at huggingface.co
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchVerified email at servicenow.com
Evan D. SherwinStanford UniversityVerified email at lbl.gov
David RolnickMcGill University, Mila Quebec AI InstituteVerified email at cs.mcgill.ca
Nikola Milojevic-DupontMCC BerlinVerified email at mcc-berlin.net
Kelly KochanskiPhD, University of Colorado - BoulderVerified email at colorado.edu
Andrew RossPhD student, Harvard UniversityVerified email at g.harvard.edu
Kris SankaranUniversity of Wisconsin - MadisonVerified email at wisc.edu
Konrad Paul KordingNathan Mossell University Professor (PIK), bioengineering & neuroscience, UPenn, CIFAR LMBVerified email at upenn.edu
Andrew NgStanford UniversityVerified email at cs.stanford.edu
Priya L. DontiAssistant Professor, MIT EECS & LIDS; Co-founder and Chair, Climate Change AIVerified email at mit.edu
Stanisław JastrzębskiChief Technology Officer & Chief Scientist @ Molecule.OneVerified email at molecule.one
Asja FischerProfessor for Machine Learning, Ruhr University BochumVerified email at ini.rub.de

Tegan Maharaj

Assistant Professor at Mila

Verified email at polymtl.ca - Homepage

Machine learning Responsible AI Deep learning Ecology Climate change


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A closer look at memorization in deep networks D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... International conference on machine learning, 233-242, 2017	2039	2017
Tackling climate change with machine learning D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ... ACM Computing Surveys (CSUR) 55 (2), 1-96, 2022	1136	2022
Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... arXiv preprint arXiv:1606.01305, 2016	386	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	381	2020
Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events E Racah, C Beckham, T Maharaj, S Ebrahimi Kahou, M Prabhat, C Pal Advances in neural information processing systems 30, 2017	290	2017
A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering T Maharaj, N Ballas, A Rohrbach, A Courville, C Pal Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	115	2017
Deep nets don't learn via memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...	73	2017
Managing AI risks in an era of rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, YN Harari, YQ Zhang, ... arXiv preprint arXiv:2310.17688, 2023	72	2023
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	68	2024
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, ... arXiv preprint arXiv:2404.09932, 2024	53	2024
Hidden incentives for auto-induced distributional shift D Krueger, T Maharaj, J Leike arXiv preprint arXiv:2009.09153, 2020	53	2020
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	52	2023
Tackling climate change with machine learning (2019) D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ... Preprint available at, 1906	50	1906
Covi white paper H Alsdurf, E Belliveau, Y Bengio, T Deleu, P Gupta, D Ippolito, R Janda, ... arXiv preprint arXiv:2005.08502, 2020	49	2020
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	38	2021
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	26	2022
Predicting infectiousness for proactive contact tracing Y Bengio, P Gupta, T Maharaj, N Rahaman, M Weiss, T Deleu, E Muller, ... arXiv preprint arXiv:2010.12536, 2020	21	2020
COVI-AgentSim: an agent-based model for evaluating methods of digital contact tracing P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, A Sharma, ... arXiv preprint arXiv:2010.16004, 2020	13	2020
Surprisal-driven zoneout K Rocki, T Kornuta, T Maharaj arXiv preprint arXiv:1610.07675, 2016	12	2016
Deep learning for detecting extreme weather patterns M Mudigonda, P Ram, K Kashinath, E Racah, A Mahesh, Y Liu, ... Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021	7	2021

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