Bayesian Theory Professors in Global

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Yanan Fan
University of New South Wales Australia
bayesian inference
bayesian computation
bayesian nonparametrics
approximate bayesian computation
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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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Daniel Roy
University of Toronto Canada
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machine learning
statistical learning theory
bayesian-frequentist interface
decision theory
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Edson Utazi
University of Southampton United Kingdom
bayesian inference
bayesian computation
machine learning
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Alexander Hartemink
Duke University Singapore
bayesian networks
bayesian statistics
machine learning
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Paul Arora
University of Toronto Canada
bayesian networks
bayesian statistics
machine learning
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Yee Teh
University of Oxford United Kingdom
bayesian statistics
bayesian nonparametrics
machine learning
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Theo Damoulas
University of Warwick United Kingdom
bayesian statistics
bayesian nonparametrics
probabilistic machine learning
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Takoua Jendoubi
University College London United Kingdom
bayesian statistics
bayesian nonparametrics
probabilistic models
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian methods
bayesian graphical models
efficient bayesian computation
approximate bayesian methods
machine learning
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Robin Ryder
Imperial College London United Kingdom
bayesian computational statistics
approximate bayesian computation
stochastic modelling
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Stephen Roberts
University of Oxford United Kingdom
bayesian statistics
machine learning
decision theory
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Zoubin Ghahramani
University of Cambridge United Kingdom
bayesian statistics
machine learning
probabilistic modelling
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Geoff Pleiss
University of British Columbia Canada
bayesian optimization
machine learning
probabilistic machine learning
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Yaozhong Hu
University of Alberta Canada
bayesian nonparametrics
probability theory
machine learning
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Nanwei Wang
University of New Brunswick Canada
bayesian model selection
machine learning
large deviations theory
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Daniel Roy
University of Toronto Canada
bayesian nonparametric statistics
machine learning
statistical learning theory
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Daniel Roy
University of Toronto Canada
bayesian nonparametric statistics
machine learning
decision theory
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Stefan Adams
University of Warwick United Kingdom
probability theory
large deviation theory
machine learning
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Lam Ho
Dalhousie University Canada
statistical theory
machine learning
stochastic modelling
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Karl Dilcher
Dalhousie University Canada
number theory
combinatorial number theory
computational number theory
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