Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio and Guillaume Lajoie
Paper (2019)
An external link is available for this itemDepartment: | Department of Mathematics and Industrial Engineering |
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PolyPublie URL: | https://publications.polymtl.ca/45967/ |
Conference Title: | 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) |
Conference Location: | Vancouver, B.-C. |
Conference Date(s): | 2019-12-08 - 2019-12-14 |
Editors: | H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche-Buc, E. Fox and R. Garnett |
Publisher: | Neural Information Processing Systems (Nips) |
Official URL: | https://papers.nips.cc/paper/9513-non-normal-recur... |
Date Deposited: | 18 Apr 2023 15:02 |
Last Modified: | 25 Sep 2024 16:34 |
Cite in APA 7: | Kerg, G., Goyette, K., Touzel, M. P., Gidel, G., Vorontsov, E., Bengio, Y., & Lajoie, G. (2019, December). Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, B.-C.. https://papers.nips.cc/paper/9513-non-normal-recurrent-neural-network-nnrnn-learning-long-time-dependencies-while-improving-expressivity-with-transient-dynamics.pdf |
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