Tegan Maharaj
Tegan Maharaj
PhD student, MILA (Polytechnique Montreal)
Verified email at polymtl.ca - Homepage
Cited by
Cited by
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
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
Tackling climate change with machine learning
D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ...
arXiv preprint arXiv:1906.05433, 2019
ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
E Racah, C Beckham, T Maharaj, SE Kahou, C Pal
arXiv preprint arXiv:1612.02095, 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
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
Deep nets don't learn via memorization
D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...
Covi white paper
H Alsdurf, E Belliveau, Y Bengio, T Deleu, P Gupta, D Ippolito, R Janda, ...
arXiv preprint arXiv:2005.08502, 2020
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
Semi-supervised detection of extreme weather events in large climate datasets
E Racah, C Beckham, T Maharaj, C Pal
Surprisal-driven zoneout
K Rocki, T Kornuta, T Maharaj
arXiv preprint arXiv:1610.07675, 2016
Hidden Incentives for Auto-Induced Distributional Shift
D Krueger, T Maharaj, J Leike
arXiv preprint arXiv:2009.09153, 2020
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
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
Misleading meta-objectives and hidden incentives for distributional shift
D Krueger, T Maharaj, S Legg, J Leike
Safe Machine Learning workshop at ICLR, 2019
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
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
Memorization in Recurrent Neural Networks
T Maharaj, D Krueger, T Coojimans
Workshop on Principled Approaches to Deep Learning, 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
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
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