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Handbook on Neural Information Processing

Overview of attention for book
Cover of 'Handbook on Neural Information Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Deep Learning of Representations
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    Chapter 2 Recurrent Neural Networks
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    Chapter 3 Supervised Neural Network Models for Processing Graphs
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    Chapter 4 Topics on Cellular Neural Networks
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    Chapter 5 Approximating Multivariable Functions by Feedforward Neural Nets
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    Chapter 6 Bochner Integrals and Neural Networks
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    Chapter 7 Semi-supervised Learning
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    Chapter 8 Statistical Relational Learning
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    Chapter 9 Kernel Methods for Structured Data
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    Chapter 10 Multiple Classifier Systems: Theory, Applications and Tools
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    Chapter 11 Self Organisation and Modal Learning: Algorithms and Applications
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    Chapter 12 Bayesian Networks, Introduction and Practical Applications
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    Chapter 13 Relevance Feedback in Content-Based Image Retrieval: A Survey
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    Chapter 14 Learning Structural Representations of Text Documents in Large Document Collections
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    Chapter 15 Neural Networks in Bioinformatics
Attention for Chapter 12: Bayesian Networks, Introduction and Practical Applications
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Citations

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65 Mendeley
Summary Dimensions citations
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Chapter title
Bayesian Networks, Introduction and Practical Applications
Chapter number 12
Book title
Handbook on Neural Information Processing
Published by
Springer, Berlin, Heidelberg, January 2013
DOI 10.1007/978-3-642-36657-4_12
Book ISBNs
978-3-64-236656-7, 978-3-64-236657-4
Authors

Wim Wiegerinck, Willem Burgers, Bert Kappen, Wiegerinck, Wim, Burgers, Willem, Kappen, Bert

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 17%
Student > Ph. D. Student 10 15%
Student > Bachelor 7 11%
Lecturer 5 8%
Student > Doctoral Student 4 6%
Other 11 17%
Unknown 17 26%
Readers by discipline Count As %
Computer Science 19 29%
Engineering 10 15%
Mathematics 5 8%
Medicine and Dentistry 2 3%
Economics, Econometrics and Finance 1 2%
Other 8 12%
Unknown 20 31%

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