Recurrent neural network

Results: 352



#Item
71A Convolutional Neural Network for Modelling Sentences Nal Kalchbrenner Edward Grefenstette  Phil Blunsom

A Convolutional Neural Network for Modelling Sentences Nal Kalchbrenner Edward Grefenstette Phil Blunsom

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Source URL: arxiv.org

Language: English - Date: 2014-04-08 20:55:10
72Recurrent Neural Net Learning and Vanishing Gradient  International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(2):107{116, 1998 Sepp Hochreiter Institut fur Informatik

Recurrent Neural Net Learning and Vanishing Gradient International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(2):107{116, 1998 Sepp Hochreiter Institut fur Informatik

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:14:24
73Structural-RNN: Deep Learning on Spatio-Temporal Graphs Ashesh Jain1,2 , Amir R. Zamir2 , Silvio Savarese2 , and Ashutosh Saxena3 Deep Recurrent Neural Network architectures, though remarkably capable at modeling sequenc

Structural-RNN: Deep Learning on Spatio-Temporal Graphs Ashesh Jain1,2 , Amir R. Zamir2 , Silvio Savarese2 , and Ashutosh Saxena3 Deep Recurrent Neural Network architectures, though remarkably capable at modeling sequenc

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Source URL: cvgl.stanford.edu

Language: English - Date: 2016-04-30 18:59:32
74Automated Abstraction of Dynamic Neural Systems for Natural Language Processing Henrik Jacobsson, Stefan L. Frank & Diego Federici Abstract— This paper presents a variant of the Crystallizing Substochastic Sequential M

Automated Abstraction of Dynamic Neural Systems for Natural Language Processing Henrik Jacobsson, Stefan L. Frank & Diego Federici Abstract— This paper presents a variant of the Crystallizing Substochastic Sequential M

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Source URL: www.stefanfrank.info

Language: English - Date: 2012-03-11 05:07:27
75Language Understanding for Text-based Games using Deep Reinforcement Learning Karthik Narasimhan∗ CSAIL, MIT

Language Understanding for Text-based Games using Deep Reinforcement Learning Karthik Narasimhan∗ CSAIL, MIT

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Source URL: www.emnlp2015.org

Language: English - Date: 2015-09-04 01:25:56
76MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Context-Sensitive and Role-Dependent Spoken Language Understanding using Bidirectional and Attention LSTMs Hori, C.; Hori, T.; Watanabe, S.; Hershey, J.R.

MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Context-Sensitive and Role-Dependent Spoken Language Understanding using Bidirectional and Attention LSTMs Hori, C.; Hori, T.; Watanabe, S.; Hershey, J.R.

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Source URL: www.merl.com

Language: English - Date: 2016-08-01 10:10:56
77A Study of the Recurrent Neural Network Encoder-Decoder for Large Vocabulary Speech Recognition Liang Lu1 , Xingxing Zhang2 , Kyunghyun Cho3 , and Steve Renals1 1  2

A Study of the Recurrent Neural Network Encoder-Decoder for Large Vocabulary Speech Recognition Liang Lu1 , Xingxing Zhang2 , Kyunghyun Cho3 , and Steve Renals1 1 2

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Source URL: www.cstr.inf.ed.ac.uk

Language: English - Date: 2015-09-29 11:06:25
78MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Driver Confusion Status Detection Using Recurrent Neural Networks Hori, C.; Watanabe, S.; Hori, T.; Harsham, B.A.; Hershey, J.R.; Koji, Y.; Fujii, Y.; Furumot

MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Driver Confusion Status Detection Using Recurrent Neural Networks Hori, C.; Watanabe, S.; Hori, T.; Harsham, B.A.; Hershey, J.R.; Koji, Y.; Fujii, Y.; Furumot

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Source URL: www.merl.com

Language: English - Date: 2016-08-02 13:09:10
79GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS Technical Note IDSIAJurgen Schmidhuber IDSIA

GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS Technical Note IDSIAJurgen Schmidhuber IDSIA

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:10:32