Artificial neural network

Results: 1863



#Item
31NCSU_SAS_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text Samuel P. Leeman-Munk James C. Lester Center for Educational Informatics North Carolina State University

NCSU_SAS_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text Samuel P. Leeman-Munk James C. Lester Center for Educational Informatics North Carolina State University

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Source URL: noisy-text.github.io

Language: English - Date: 2016-08-14 21:11:09
32Quantifying Generalization in Linearly Weighted Neural Networks (Short title: Quantifying Generalization) Martin Anthony1 and Sean B. Holden2  Abstract

Quantifying Generalization in Linearly Weighted Neural Networks (Short title: Quantifying Generalization) Martin Anthony1 and Sean B. Holden2 Abstract

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Source URL: www.maths.lse.ac.uk

Language: English - Date: 2000-04-03 14:52:08
33INRIA_SCIENTIFIQUE_FR_CMJN

INRIA_SCIENTIFIQUE_FR_CMJN

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Source URL: lareg.ensg.ign.fr

Language: English - Date: 2016-04-19 10:29:57
34Image source: Yury V. Zaytsev  NEST: The Neural Simulation Tool PARTNERS

Image source: Yury V. Zaytsev NEST: The Neural Simulation Tool PARTNERS

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Source URL: www.nest-simulator.org

Language: English - Date: 2016-01-04 09:55:18
35A Hybrid System for MorphoSyntactic Disambiguation in Bulgarian Kiril Iv. Simov and Petya N. Osenova  y

A Hybrid System for MorphoSyntactic Disambiguation in Bulgarian Kiril Iv. Simov and Petya N. Osenova y

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Source URL: bultreebank.org

Language: English - Date: 2003-12-07 15:22:49
36Chapter 2 I nducti ve Learni ng This chapter presents an overview of the research in inductive learning. We briefly describe the various aspects of this scientific field and present some examples of applications. We the

Chapter 2 I nducti ve Learni ng This chapter presents an overview of the research in inductive learning. We briefly describe the various aspects of this scientific field and present some examples of applications. We the

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Source URL: www.dcc.fc.up.pt

Language: English - Date: 2012-12-13 10:18:43
37Connection Science Vol. 18, No. 3, September 2006, 287–302 Learn more by training less: systematicity in sentence processing by recurrent networks STEFAN L. FRANK*

Connection Science Vol. 18, No. 3, September 2006, 287–302 Learn more by training less: systematicity in sentence processing by recurrent networks STEFAN L. FRANK*

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Source URL: www.stefanfrank.info

Language: English - Date: 2012-03-11 05:06:36
38Why Form-Meaning Mappings are not Entirely Arbitrary in Language Padraic Monaghan () Department of Psychology, University of York York, YO10 5DD, UK  Morten H. Christiansen ()

Why Form-Meaning Mappings are not Entirely Arbitrary in Language Padraic Monaghan () Department of Psychology, University of York York, YO10 5DD, UK Morten H. Christiansen ()

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Source URL: cnl.psych.cornell.edu

Language: English - Date: 2007-11-10 12:47:00
39Published at International Joint Conference on Neural Networks (IJCNN), 2015  Recurrent Convolutional Neural Networks for Object-Class Segmentation of RGB-D Video Mircea Serban Pavel, Hannes Schulz, and Sven Behnke Unive

Published at International Joint Conference on Neural Networks (IJCNN), 2015 Recurrent Convolutional Neural Networks for Object-Class Segmentation of RGB-D Video Mircea Serban Pavel, Hannes Schulz, and Sven Behnke Unive

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Source URL: www.ais.uni-bonn.de

Language: English - Date: 2015-08-14 09:34:45
40International Journal of Geographical Information Science  ee rP Fo

International Journal of Geographical Information Science ee rP Fo

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Source URL: www.public.asu.edu

Language: English - Date: 2012-08-12 23:21:04