Dropout improves Recurrent Neural Networks for Handwriting Recognition

5 November 2013

Papers citing "Dropout improves Recurrent Neural Networks for Handwriting Recognition"

8 / 58 papers shown

Title
Recurrent Memory Networks for Language Modeling Ke M. Tran Arianna Bisazza Christof Monz 30 21 0 06 Jan 2016
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks Y. Gal Zoubin Ghahramani UQCV DRL BDL 17 1,642 0 16 Dec 2015
Named Entity Recognition with Bidirectional LSTM-CNNs Jason P. C. Chiu Eric Nichols 17 1,888 0 26 Nov 2015
Multi-task Sequence to Sequence Learning Minh-Thang Luong Quoc V. Le Ilya Sutskever Oriol Vinyals Lukasz Kaiser AIMat 36 806 0 19 Nov 2015
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation Marijn F. Stollenga Wonmin Byeon Marcus Liwicki Jürgen Schmidhuber 16 294 0 24 Jun 2015
Learning to Execute Wojciech Zaremba Ilya Sutskever ODL 36 555 0 17 Oct 2014
Recurrent Neural Network Regularization Wojciech Zaremba Ilya Sutskever Oriol Vinyals ODL 32 2,758 0 08 Sep 2014
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012