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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Madan, K., Ke, N. R., Goyal, A., Schölkopf, B., & Bengio, Y. (2021, April). Fast and slow learning of recurrent independent mechanisms [Paper]. 10th International Conference on Learning Representations (ICLR 2021) (18 pages). Unavailable
Bengio, Y., Deleu, T., Rahaman, N., Ke, N. R., Lachapelle, S., Bilaniuk, O., Goyal, A., & Pal, C. J. (2020, April). A meta-transfer objective for learning to disentagle causal mechanisms [Paper]. 8th International Conference on Learning Representations (ICLR 2020), Addis Ababa, Ethiopia (27 pages). External link
Krueger, D., Maharaj, T., Kramar, J., Pezeshki, M., Ballas, N., Ke, N. R., Goyal, A., Bengio, Y., Courville, A., & Pal, C. J. (2017, April). Zoneout: Regularizing rNNs by randomly preserving hidden activations [Paper]. 5th International Conference on Learning Representations (ICLR 2017), Toulon, France (11 pages). External link
Henderson, P., Sinha, K., Angelard-Gontier, N., Ke, N. R., Fried, G., Lowe, R., & Pineau, J. (2018, February). Ethical Challenges in Data-Driven Dialogue Systems [Paper]. 1st AAAI/ACM Conference on AI, Ethics, and Society (AIES 2018), New Orleans, LA. External link
Ke, N. R., Zoma, K., Sordoni, A., Lin, Z., Trischler, A., Bengio, Y., Pineau, J., Charlin, L., & Pal, C. J. (2018, July). Focused hierarchical RNNs for conditional sequence processing [Paper]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. External link
Ke, N. R., Goyal, A., Bilaniuk, O., Binas, J., Mozer, M. C., Pal, C. J., & Bengio, Y. (2018, December). Sparse attentive backtracking: Temporal credit assignment through reminding [Paper]. 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montréal, Canada (12 pages). External link
Serdyuk, D., Ke, N. R., Sordoni, A., Trischler, A., Pal, C. J., & Bengio, Y. (2018, April). Twin Networks: Matching the future for sequence generation [Paper]. 6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada (12 pages). External link
Goyal, A., Ke, N. R., Ganguli, S., & Bengio, Y. (2017, December). Variational walkback: Learning a transition operator as a stochastic recurrent net [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA. Unavailable
Goyal, A., Sordoni, A., Cote, M.-A., Ke, N. R., & Bengio, Y. (2017, December). Z-forcing: Training stochastic recurrent networks [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA. Unavailable
