Bayesian Model Calibration Professors in Global

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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
approximate bayesian methods
bayesian methods
efficient bayesian computation
hierarchical modeling
machine learning
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Yanan Fan
University of New South Wales Australia
bayesian computation
approximate bayesian computation
bayesian inference
bayesian nonparametrics
spatial modelling
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Mayank Chadha
University of California, San Diego United States of America
bayesian optimization
bayesian decision theory
geometrically exact modeling
machine learning
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Sharmistha Guha
Texas A&M University United States of America
bayesian high dimensional regression
bayesian object-oriented regression
bayesian nonparametric mixture models
bayesian causal inference
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Peter Mueller
University of Texas at Austin United States of America
bayesian bioinformatics
bayesian adaptive clinical trial design
nonparametric bayesian inference
computational methods in bayesian inference
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Prasanth Nair
University of Toronto Institute for Aerospace Studies Canada
bayesian model calibration
computational modeling
machine learning
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Michele Guindani
University of California, Irvine United States of America
bayesian modeling
nonparametric bayesian models
machine learning
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Umberto Picchini
University of Gothenburg Sweden
approximate bayesian computation
bayesian computational methods
stochastic modelling
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Edson Utazi
University of Southampton United Kingdom
bayesian computation
bayesian inference
machine learning
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Trevor Campbell
University of British Columbia Canada
bayesian inference
bayesian theory
bayesian nonparametrics
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Umberto Picchini
Chalmers University of Technology Sweden
approximate bayesian computation
bayesian computational methods
stochastic modelling
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Robin Ryder
Imperial College London United Kingdom
approximate bayesian computation
bayesian computational statistics
stochastic modelling
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Andrew Mccluskey
University of Bristol United Kingdom
bayesian analysis
mathematical modeling
statistical modeling
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Charbel Farhat
Stanford University United States of America
bayesian optimization
mathematical models
probabilistic machine learning
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Daniel Laydon
Imperial College London United Kingdom
bayesian statistics
mathematical modelling
stochastic modelling
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Hina Shaheen
University of Manitoba Canada
bayesian inference
computational modelling
machine learning
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Geoff Pleiss
University of British Columbia Canada
bayesian optimization
machine learning
probabilistic machine learning
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Olga Vitek
Purdue University United States of America
bayesian analysis
combinatorial optimization
machine learning
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Alexander Hartemink
Duke University Singapore
bayesian networks
bayesian statistics
machine learning
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Jaehee Kim
Cornell University Netherlands
bayesian inference
mathematical models
machine learning
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Theo Damoulas
University of Warwick United Kingdom
bayesian statistics
bayesian nonparametrics
probabilistic machine learning
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