Contains fulltext : 205646.pdf (publisher's version ) (Open Access
This dissertation attempts to gather the main research topics I engaged during the past four years, ...
Some key features of hierarchical models are: • data (possibly multiple data sources) are related vi...
In previous work [3] we have proposed Hierarchical Bayesian Networks (HBNs) as an extension of Bay...
Computational modeling plays an important role in modern neuroscience research. Much previous resear...
Bayesian data analysis involves describing data by meaningful mathematical models, and allocating cr...
Introduction: The need for hierarchical models Those of us who study human cognition have no easy ta...
Contains fulltext : 34584.pdf (preprint version ) (Open Access
Across the sciences, social sciences and engineering, applied statisticians seek to build understand...
Bayesian hypothesis testing for hierarchical models is greatly facilitated by the use of sophisticat...
This thesis focuses on the application of the hierarchical Bayesian (HB) methodology to real data. T...
• Bayesian mixed-effects inference for group studies (i) models within-subject and across-subjects u...
Details of the data analyzed using our proposed Bayesian hierarchical model for combining sources at...
Research in cognitive psychology often focuses on how people deal with multiple sources of informati...
Appropriate tools for managing large-scale data, like online texts, images and user pro-files, are b...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/170955/1/sim9168.pdfhttp://deepblue.lib...
This dissertation attempts to gather the main research topics I engaged during the past four years, ...
Some key features of hierarchical models are: • data (possibly multiple data sources) are related vi...
In previous work [3] we have proposed Hierarchical Bayesian Networks (HBNs) as an extension of Bay...
Computational modeling plays an important role in modern neuroscience research. Much previous resear...
Bayesian data analysis involves describing data by meaningful mathematical models, and allocating cr...
Introduction: The need for hierarchical models Those of us who study human cognition have no easy ta...
Contains fulltext : 34584.pdf (preprint version ) (Open Access
Across the sciences, social sciences and engineering, applied statisticians seek to build understand...
Bayesian hypothesis testing for hierarchical models is greatly facilitated by the use of sophisticat...
This thesis focuses on the application of the hierarchical Bayesian (HB) methodology to real data. T...
• Bayesian mixed-effects inference for group studies (i) models within-subject and across-subjects u...
Details of the data analyzed using our proposed Bayesian hierarchical model for combining sources at...
Research in cognitive psychology often focuses on how people deal with multiple sources of informati...
Appropriate tools for managing large-scale data, like online texts, images and user pro-files, are b...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/170955/1/sim9168.pdfhttp://deepblue.lib...
This dissertation attempts to gather the main research topics I engaged during the past four years, ...
Some key features of hierarchical models are: • data (possibly multiple data sources) are related vi...
In previous work [3] we have proposed Hierarchical Bayesian Networks (HBNs) as an extension of Bay...
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