Bayesian Learning for Neural Networks

The Bayesian neural network model with two hidden layers of six units performed
substantially better than any of the other methods. To do a formal test for the
significance of the difference in average performance seen, one would need the
 ...

Bayesian Learning for Neural Networks

Bayesian Learning for Neural Networks

Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

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Bayesian Learning for Neural Networks
Language: en
Pages: 204
Authors: Radford M. Neal
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of
Enhanced Bayesian Network Models for Spatial Time Series Prediction
Language: en
Pages: 149
Authors: Monidipa Das, Soumya K. Ghosh
Categories: Technology & Engineering
Type: BOOK - Published: 2019-11-07 - Publisher: Springer Nature

This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. The monograph is primarily prepared
Advances in Biometric Person Authentication
Language: en
Pages: 699
Authors: Stan Z. Li
Categories: Business & Economics
Type: BOOK - Published: 2004-11-29 - Publisher: Springer Science & Business Media

This book constitutes the refereed proceedings of the 5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004, held in Guanzhou, China in December 2004. The 60 revised full papers presented together with 14 invited papers by internationally leading researchers were carefully reviewed and selected from 140 submissions. The papers are organized
Bayesian Networks
Language: en
Pages: 446
Authors: Olivier Pourret, Patrick Naïm, Bruce Marcot
Categories: Mathematics
Type: BOOK - Published: 2008-05-05 - Publisher: John Wiley & Sons

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating
Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards
Language: en
Pages:
Authors: Olivier Pourret, Patrick Naïm, Bruce Marcot
Categories: Dissertations, Academic
Type: BOOK - Published: 2008 - Publisher:

Books about Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards

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