On Fast Dropout and its Applicability to Recurrent Networks

4 November 2013

Papers citing "On Fast Dropout and its Applicability to Recurrent Networks"

9 / 9 papers shown

Title
How to Construct Deep Recurrent Neural Networks Razvan Pascanu Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 116 1,009 0 20 Dec 2013
Generating Sequences With Recurrent Neural Networks Alex Graves GAN 146 4,033 0 04 Aug 2013
Dropout Training as Adaptive Regularization Stefan Wager Sida I. Wang Percy Liang 129 599 0 04 Jul 2013
Speech Recognition with Deep Recurrent Neural Networks Alex Graves Abdel-rahman Mohamed Geoffrey E. Hinton 224 8,513 0 22 Mar 2013
Regularization and nonlinearities for neural language models: when are they needed? Marius Pachitariu M. Sahani 78 46 0 23 Jan 2013
High-dimensional sequence transduction Nicolas Boulanger-Lewandowski Yoshua Bengio Pascal Vincent AI4TS 182 69 0 09 Dec 2012
Advances in Optimizing Recurrent Networks Yoshua Bengio Nicolas Boulanger-Lewandowski Razvan Pascanu ODL 102 522 0 04 Dec 2012
On the difficulty of training Recurrent Neural Networks Razvan Pascanu Tomas Mikolov Yoshua Bengio ODL 190 5,342 0 21 Nov 2012
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 447 7,661 0 03 Jul 2012