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
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
Lynn H. KaackHertie SchoolVerified email at hertie-school.org
Natasha JaquesGoogle Research, UC BerkeleyVerified 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 stanford.edu
David RolnickMcGill University, Mila Quebec AI InstituteVerified email at cs.mcgill.ca
Nikola Milojevic-DupontTechnical University 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
Konrad Paul KordingNathan Mossell University Professor (PIK), bioengineering & neuroscience, UPenn, CIFAR LMBVerified email at upenn.edu

Tegan Maharaj

Assistant Professor at University of Toronto

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	1633	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	795	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	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
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	248	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	101	2017
Deep nets don't learn via memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...	63	2017
Covi white paper H Alsdurf, E Belliveau, Y Bengio, T Deleu, P Gupta, D Ippolito, R Janda, ... arXiv preprint arXiv:2005.08502, 2020	48	2020
Tackling climate change with machine learning (2019) D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ... arXiv preprint arxiv:1906.05433, 1906	45	1906
Hidden incentives for auto-induced distributional shift D Krueger, T Maharaj, J Leike arXiv preprint arXiv:2009.09153, 2020	39	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	23	2021
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	20	2020
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
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	11	2020
Surprisal-driven zoneout K Rocki, T Kornuta, T Maharaj arXiv preprint arXiv:1610.07675, 2016	11	2016
Deep learning for extreme weather detection M Prabhat, E Racah, J Biard, Y Liu, M Mudigonda, K Kashinath, ... AGU Fall Meeting Abstracts 2017, IN11A-0022, 2017	7	2017
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	5	2021
Misleading meta-objectives and hidden incentives for distributional shift D Krueger, T Maharaj, S Legg, J Leike Workshop on Safe Machine Learning at the 7th International Conference on …, 2019	5	2019
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	4	2023

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