Tegan Maharaj

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David Scott KruegerUniversity Lecturer, University of Cambridge; PhD Student, University of MontrealVerified email at umontreal.ca
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 BallasFacebook AI ResearchVerified email at fb.com
Aaron CourvilleAssociate Professor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
Stanisław JastrzębskiCTO 👨💻 & CSO 🧪 @ Molecule.OneVerified email at molecule.one
Devansh ArpitSenior Research Scientist, SalesforceVerified email at salesforce.com
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
Christopher BeckhamInstitut Québécois d'Intelligence ArtificielleVerified email at polymtl.ca
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaVerified email at iro.umontreal.ca
Lynn H. KaackHertie SchoolVerified email at hertie-school.org
Natasha JaquesGoogle Research, UC BerkeleyVerified email at google.com
Alexandra (Sasha) LuccioniUniversité de Montréal and MilaVerified email at mila.quebec
Evan D. SherwinStanford UniversityVerified email at stanford.edu
David RolnickMcGill University, Mila Quebec AI InstituteVerified email at cs.mcgill.ca
Nikola Milojevic-DupontMercator Research Institute on Global Commons and Climate Change (MCC)Verified 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

Tegan Maharaj

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	923	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	356*	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	298	2016
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	140	2017
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	128	2020
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	62	2017
Deep nets don't learn via memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...	55	2017
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	26	1906
Covi white paper H Alsdurf, E Belliveau, Y Bengio, T Deleu, P Gupta, D Ippolito, R Janda, ... arXiv preprint arXiv:2005.08502, 2020	25	2020
Prabhat, and C. Pal, 2017: ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events E Racah, C Beckham, T Maharaj, S Kahou Advances in Neural Information Processing Systems 2017, 3403-3414, 2017	25	2017
Semi-supervised detection of extreme weather events in large climate datasets E Racah, C Beckham, T Maharaj, C Pal	18	2016
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) 5, 2017	16	2017
Hidden incentives for auto-induced distributional shift D Krueger, T Maharaj, J Leike arXiv preprint arXiv:2009.09153, 2020	12	2020
Surprisal-driven zoneout K Rocki, T Kornuta, T Maharaj arXiv preprint arXiv:1610.07675, 2016	8	2016
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	7	2020
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	5	2017
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	3	2021
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	3	2020
Misleading meta-objectives and hidden incentives for distributional shift D Krueger, T Maharaj, S Legg, J Leike Safe Machine Learning workshop at ICLR, 2019	3	2019
ClimateNet: a machine learning dataset for climate science research M Prabhat, J Biard, S Ganguly, S Ames, K Kashinath, SK Kim, S Kahou, ... AGU fall meeting abstracts 2017, IN13E-01, 2017	3	2017

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