Tegan Maharaj

引用先

	すべて	2019 年以来
引用	5293	4998
h 指標	17	17
i10 指標	19	18

1400

700

350

1050

20162017201820192020202120222023202418 77 162 313 516 707 920 1103 1400

オープンアクセス

すべて表示

7 件の論文

0 件の論文

利用可能

利用不可

助成機関の要件に基づく

共著者

David Scott KruegerUniversity Assistant Professor, University of Cambridge確認したメールアドレス: cam.ac.uk
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFAR確認したメールアドレス: umontreal.ca
Chris PalProfessor, Polytechnique Montréal & Mila, ServiceNow Research, Canada CIFAR AI Chair確認したメールアドレス: polymtl.ca
Nicolas BallasMeta AI Research確認したメールアドレス: meta.com
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chair確認したメールアドレス: umontreal.ca
Lynn H. KaackHertie School確認したメールアドレス: hertie-school.org
Natasha JaquesUniversity of Washington, Google Research確認したメールアドレス: google.com
Sasha LuccioniHugging Face確認したメールアドレス: huggingface.co
Alexandre LacosteStaff Research Scientist, ServiceNow Research確認したメールアドレス: servicenow.com
Evan D. SherwinLawrence Berkeley National Laboratory確認したメールアドレス: lbl.gov
David RolnickMcGill University, Mila Quebec AI Institute確認したメールアドレス: cs.mcgill.ca
Nikola Milojevic-DupontMCC Berlin確認したメールアドレス: mcc-berlin.net
Kelly KochanskiPhD, University of Colorado - Boulder確認したメールアドレス: colorado.edu
Andrew RossPhD student, Harvard University確認したメールアドレス: g.harvard.edu
Kris SankaranUniversity of Wisconsin - Madison確認したメールアドレス: wisc.edu
Konrad Paul KordingNathan Mossell University Professor (PIK), bioengineering & neuroscience, UPenn, CIFAR LMB確認したメールアドレス: upenn.edu
Andrew NgStanford University確認したメールアドレス: cs.stanford.edu
Priya L. DontiAssistant Professor, MIT EECS & LIDS; Co-founder and Chair, Climate Change AI確認したメールアドレス: mit.edu
Anna Waldman-BrownMIT Industrial Performance Center確認したメールアドレス: alum.mit.edu
Stanisław JastrzębskiChief Technology Officer & Chief Scientist @ Molecule.One確認したメールアドレス: molecule.one

フォロー

Tegan Maharaj

Assistant Professor at Mila

確認したメールアドレス: polymtl.ca - ホームページ

Machine learning Responsible AI Deep learning Ecology Climate change


タイトル引用回数順公開年順タイトル順	引用先引用先	年
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	2123	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	1202	2022
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	413	2020
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	387	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	295	2017
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	120	2024
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	117	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, ... arXiv preprint arXiv:2404.09932, 2024	88	2024
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, 18, 2023	80	2023
Deep nets don't learn via memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...	75	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	69	2023
Hidden incentives for auto-induced distributional shift D Krueger, T Maharaj, J Leike arXiv preprint arXiv:2009.09153, 2020	56	2020
Tackling climate change with machine learning (2019) D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ... Preprint available at, 1906	53	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	43	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	22	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
Proactive contact tracing P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, N Minoyan, ... PLOS Digital Health 2 (3), e0000199, 2023	7	2023

現在システムで処理を実行できません。しばらくしてからもう一度お試しください。

論文 1–20

年間引用数

重複した引用

結合された引用

共著者を追加共著者

フォロー

引用先

共著者