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A Practical Bayesian Framework for Backprop Networks (1991)
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David J.C. MacKay
| Venue: | Neural Computation |
| Citations: | 494 - 19 self |
BibTeX
@ARTICLE{MacKay91apractical,
author = {David J.C. MacKay},
title = {A Practical Bayesian Framework for Backprop Networks},
journal = {Neural Computation},
year = {1991},
volume = {4},
pages = {448--472}
}
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Abstract
A quantitative and practical Bayesian framework is described for learning of mappings in feedforward networks. The framework makes possible: (1) objective comparisons between solutions using alternative network architectures
