Results 301 to 310 of about 157,640 (328)

Hierarchical Bayesian models of cognitive development

Biological Cybernetics, 2016
This article provides an introductory overview of the state of research on Hierarchical Bayesian Modeling in cognitive development. First, a brief historical summary and a definition of hierarchies in Bayesian modeling are given. Subsequently, some model structures are described based on four examples in the literature.
Thomas Glassen, Verena Nitsch
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AUC Maximization in Bayesian Hierarchical Models

2016
The area under the curve (AUC) measures such as the area under the receiver operating characteristics curve (AUROC) and the area under the precision-recall curve (AUPR) are known to be more appropriate than the error rate, especially, for imbalanced data sets.
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A hierarchical Bayesian model for pattern recognition

The 2012 International Joint Conference on Neural Networks (IJCNN), 2012
The success of automated classification hinges on the choice of the representation of the data. Much research has focused on feature extraction techniques that can identify highly informative representations of a dataset. In this paper, we adapt for the purposes of classification a hierarchical Bayesian model developed by Karklin and Lewicki to model ...
Ashwini Shikaripur Nadig, Brian Potetz
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Bayesian Hierarchical Models for Subgroup Analysis

Pharmaceutical Statistics
ABSTRACTIn conventional subgroup analyses, subgroup treatment effects are estimated using data from each subgroup separately without considering data from other subgroups in the same study. The subgroup treatment effects estimated this way may be heterogenous with high variability due to small sample sizes in some subgroups and much different from the ...
Yun Wang, Wenda Tu, William Koh, James Travis, Robert Abugov, Kiya Hamilton, Mengjie Zheng, Roberto Crackel, Pablo Bonangelino, Mark Rothmann   +9 more
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Bayesian Hierarchical Models

JAMA, 2018
Anna E, McGlothlin, Kert, Viele
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Unsupervised Grouped Axial Data Modeling via Hierarchical Bayesian Nonparametric Models With Watson Distributions

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Wentao Fan, Nizar Bouguila, Lin Yang
exaly  

Hierarchical Bayesian learning framework for multi-level modeling using multi-level data

Mechanical Systems and Signal Processing, 2022
Xinyu Jia, Costas Papadimitriou
exaly  

Hierarchical Bayesian modeling framework for model updating and robust predictions in structural dynamics using modal features

Mechanical Systems and Signal Processing, 2022
Xinyu Jia, Omid Sedehi, Costas Papadimitriou   +2 more
exaly  

Nonlinear model updating through a hierarchical Bayesian modeling framework

Computer Methods in Applied Mechanics and Engineering, 2022
Xinyu Jia, Omid Sedehi, Costas Papadimitriou   +2 more
exaly  

Bayesian Network Structure Inference with an Hierarchical Bayesian Model

2010
Bayesian Networks (BNs) are applied to a wide range of applications. In the past few years great interest is dedicated to the problem of inferring the structure of BNs solely from the data. In this work we explore a probabilistic method which enables the inclusion of extra knowledge in the inference of BNs.
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