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36
Bayesian Mean Field Algorithms for Neural Networks and Gaussian Processes
, 1998
"... The subject of this thesis is the derivation and study of Bayesian mean field learning algorithms for feed-forward neural networks and Gaussian processes. In Bayes learning our posterior beliefs -- based upon our a priori knowledge and past observations -- are expressed as probabilities. Making pred ..."
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Cited by 6 (0 self)
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The subject of this thesis is the derivation and study of Bayesian mean field learning algorithms for feed-forward neural networks and Gaussian processes. In Bayes learning our posterior beliefs -- based upon our a priori knowledge and past observations -- are expressed as probabilities. Making
Classification of Lithofacies Boundaries Using the KTB Borehole Data: A Bayesian Neural Network Modeling
"... A novel approach based on the concept of Bayesian neural network learning theory is developed and applied to German Continental Deep Drilling Program (KTB) well log signal for classification of lithofacies boundaries. We parameterized different combination of synthetic model to match with the publis ..."
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A novel approach based on the concept of Bayesian neural network learning theory is developed and applied to German Continental Deep Drilling Program (KTB) well log signal for classification of lithofacies boundaries. We parameterized different combination of synthetic model to match
unknown title
"... Anne SABOURIN Mélanges bayésiens de modèles d'extrêmes multivariés, Application à la prédétermination régionale des crues avec données incomplètes. Sous la direction de: ..."
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Anne SABOURIN Mélanges bayésiens de modèles d'extrêmes multivariés, Application à la prédétermination régionale des crues avec données incomplètes. Sous la direction de:
Active Mask Framework for Segmentation of Fluorescence Microscope Images
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol
Subspace Communication
, 2014
"... We are surrounded by electronic devices that take advantage of wireless technologies, from our computer mice, which require little amounts of information, to our cellphones, which demand increasingly higher data rates. Until today, the coexistence of such a variety of services has been guaranteed by ..."
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We are surrounded by electronic devices that take advantage of wireless technologies, from our computer mice, which require little amounts of information, to our cellphones, which demand increasingly higher data rates. Until today, the coexistence of such a variety of services has been guaranteed
3esis Supervisor Accepted by
, 2005
"... in partial ful2llment of the requirements for the degree of ..."
© Institute of Mathematical Statistics, 2012 Statistical Modeling of Spatial Extremes1
"... Abstract. The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This ar-ticle reviews recent progress in the statistical modeling of spatial e ..."
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on rain-fall in Switzerland. Whereas latent variable modeling allows a better fit to marginal distributions, it fits the joint distributions of extremes poorly, so appropriately-chosen copula or max-stable models seem essential for suc-cessful spatial modeling of extremes.
Results 1 - 10
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36