| A closer look at memorization in deep networks D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 188 | 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 | 157 | 2016 |
| 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, M Prabhat, C Pal Advances in Neural Information Processing Systems, 3402-3413, 2017 | 38 | 2017 |
| Deep Nets Don't Learn via Memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ... | 21 | 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 | 21 | 2017 |
| Tackling Climate Change with Machine Learning D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ... arXiv preprint arXiv:1906.05433, 2019 | 16* | 2019 |
| 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). https://arxiv. org/abs …, 2017 | 11 | 2017 |
| Semi-supervised detection of extreme weather events in large climate datasets E Racah, C Beckham, T Maharaj, C Pal arXiv preprint arXiv:1612.02095, 2016 | 11 | 2016 |
| Surprisal-driven zoneout K Rocki, T Kornuta, T Maharaj arXiv preprint arXiv:1610.07675, 2016 | 7 | 2016 |
| Deep Learning for Extreme Weather Detection M Prabhat, E Racah, J Biard, Y Liu, M Mudigonda, K Kashinath, ... AGU Fall Meeting Abstracts, 2017 | 1 | 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 | 1 | 2017 |
| Deep Learning recognizes weather and climate patterns K Kashinath, M Prabhat, M Mudigonda, A Mahesh, SK Kim, Y Liu, ... AGU Fall Meeting Abstracts, 2018 | | 2018 |
| Reserve Output Units for Deep Open-Set Learning T Maharaj, D Krueger | | 2018 |
| PRACTICAL APPLICATIONS OF BIOLOGICAL REALISM IN ARTIFICIAL NEURAL NETWORKS T MAHARAJ | | 2015 |
| MISLEADING META-OBJECTIVES AND HIDDEN INCEN-TIVES FOR DISTRIBUTIONAL SHIFT D Krueger, T Maharaj, S Legg, J Leike | | |
| Memorization in Recurrent Neural Networks T Maharaj, D Krueger, T Coojimans | | |
David Scott KruegerPhD Student, University of MontrealVerified email at umontreal.ca
