Bayesian Integrated Modeling Professors in Global

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Peter Mueller
University of Texas at Austin United States of America
bayesian bioinformatics
nonparametric bayesian inference
computational methods in bayesian inference
bayesian adaptive clinical trial design
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Sara Hamis
Uppsala University Sweden
bayesian statistics
mathematical modelling
machine learning
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
bayesian methods
efficient bayesian computation
machine learning
approximate bayesian methods
hierarchical modeling
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Veronika Rockova
University of Chicago United States of America
bayesian statistics
machine learning
predictive inference
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Jafet Belmont Osuna
University of Glasgow United Kingdom
bayesian methods
machine learning
statistical models
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Luke Miller
Radboud University Netherlands
computational modeling
machine learning
neural network modeling
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Michael Pyrcz
University of Texas at Austin United States of America
multivariate modeling
machine learning
spatiotemporal modeling
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Edson Utazi
University of Southampton United Kingdom
bayesian computation
bayesian inference
spatial modeling
machine learning
spatiotemporal modeling
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Alan Yuille
Johns Hopkins University United States of America
mathematical models
machine learning
computational models
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Somnath Ghosh
Johns Hopkins University United States of America
machine learning
multiscale modeling
multi-physics modeling
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Jamal Arsanjani
Aalborg University Denmark
machine learning
geospatial modelling
statistical models
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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David Ring
University of Washington United States of America
bayesian simulations
machine learning
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Robin Evans
University of Oxford United Kingdom
bayesian network models
multivariate statistical models
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Daniel Laydon
Imperial College London United Kingdom
bayesian statistics
stochastic modelling
mathematical modelling
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Serge Dubuc
University of Montreal Canada
bayesian statistics
mathematical modelling
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Rob Van Beers
Vrije Universiteit Amsterdam Netherlands
bayesian methods
computational modeling
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Georg Gerber
Harvard-MIT Health Sciences Technology United States of America
bayesian dynamical systems
machine learning
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Eric Schwartz
University of Michigan United States of America
bayesian statistics
machine learning
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Catherine Calder
University of Texas at Austin United States of America
bayesian statistics
machine learning
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