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1606.01305
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Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
International Conference on Learning Representations (ICLR), 2016
3 June 2016
David M. Krueger
Tegan Maharaj
János Kramár
Mohammad Pezeshki
Nicolas Ballas
Nan Rosemary Ke
Anirudh Goyal
Yoshua Bengio
Aaron Courville
C. Pal
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Papers citing
"Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations"
50 / 180 papers shown
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Daria Soboleva
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End-to-End Spoken Language Understanding Without Full Transcripts
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Scheduled DropHead: A Regularization Method for Transformer Models
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13 Feb 2020
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Snoopy: Sniffing Your Smartwatch Passwords via Deep Sequence Learning
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Improving the Gating Mechanism of Recurrent Neural Networks
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Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics
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High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
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Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks
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Recurrent Independent Mechanisms
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The Neural State Pushdown Automata
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Non-local Recurrent Neural Memory for Supervised Sequence Modeling
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