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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers.

A. Lamb, A. Goyal, A. Slowik, M. Mozer, P. Beaudoin, and Y. Bengio. CoRR, (2020)

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Metric-based model selection for time-series forecasting.Y. Bengio, and N. Chapados. NNSP, page 13-22. IEEE, (2002)On the difficulty of training Recurrent Neural NetworksR. Pascanu, T. Mikolov, and Y. Bengio. (2012)cite arxiv:1211.5063Comment: Improved description of the exploding gradient problem and description and analysis of the vanishing gradient problem.FigureQA: An Annotated Figure Dataset for Visual Reasoning.S. Kahou, A. Atkinson, V. Michalski, Á. Kádár, A. Trischler, and Y. Bengio. CoRR, (2017)Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep ExtensionsH. Luo, P. Carrier, A. Courville, and Y. Bengio. CoRR, (2012)Unsupervised Feature Learning and Deep Learning: A Review and New PerspectivesY. Bengio, A. Courville, and P. Vincent. CoRR, (2012)A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues.I. Serban, A. Sordoni, R. Lowe, L. Charlin, J. Pineau, A. Courville, and Y. Bengio. CoRR, (2016)An Actor-Critic Algorithm for Sequence Prediction.D. Bahdanau, P. Brakel, K. Xu, A. Goyal, R. Lowe, J. Pineau, A. Courville, and Y. Bengio. CoRR, (2016)Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations.A. Lamb, J. Binas, A. Goyal, D. Serdyuk, S. Subramanian, I. Mitliagkas, and Y. Bengio. CoRR, (2018)Count-ception: Counting by Fully Convolutional Redundant Counting.J. Cohen, H. Lo, and Y. Bengio. CoRR, (2017)Towards Biologically Plausible Deep Learning.Y. Bengio, D. Lee, J. Bornschein, and Z. Lin. CoRR, (2015)

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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers.

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Disambiguation of "Bengio, Yoshua"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers.

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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers.