Bayesian Data Assimilation Professors in Global

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Yee Teh
University of Oxford United Kingdom
bayesian statistics
bayesian nonparametrics
machine learning
large scale machine learning
deep learning
probabilistic learning
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John Quilty
University of Waterloo Canada
data assimilation
machine learning
data mining
data-driven modelling
deep learning
ensemble modelling
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
bayesian methods
approximate bayesian methods
efficient bayesian computation
machine learning
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Dabao Zhang
Purdue University United States of America
bayesian
machine learning
data mining
statistical inference
massive data modeling
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Yanan Fan
University of New South Wales Australia
bayesian computation
bayesian inference
approximate bayesian computation
bayesian nonparametrics
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Sharmistha Guha
Texas A&M University United States of America
bayesian high dimensional regression
bayesian causal inference
bayesian object-oriented regression
bayesian nonparametric mixture models
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Bojana Rosic
University of Twente Netherlands
data assimilation
machine learning
data analysis
statistical inference
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Umberto Picchini
Chalmers University of Technology Sweden
approximate bayesian computation
bayesian computational methods
stochastic modelling
statistical inference
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Hina Shaheen
University of Manitoba Canada
bayesian inference
machine learning
data analysis
statistical machine learning
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Olga Vitek
Purdue University United States of America
bayesian analysis
machine learning
data analysis
statistical inference
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Umberto Picchini
University of Gothenburg Sweden
approximate bayesian computation
bayesian computational methods
stochastic modelling
statistical inference
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John Lau
University of Western Australia Australia
bayesian statistics
bayesian nonparametric statistics
statistical filtering
statistical clustering
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Qifan Song
Purdue University United States of America
bayesian data science
machine learning
deep learning
massive data modeling
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Andrew Casey
Monash University Australia
bayesian statistics
machine learning
data analysis
deep learning
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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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Michael Zhu
Purdue University United States of America
bayesian computational methods
machine learning
data mining
statistical inference
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Yiyu Yao
University of Regina Canada
machine learning
data analysis
data mining
data analytics
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Tom Rainforth
University of Oxford United Kingdom
bayesian experimental design
statistical machine learning
deep learning
approximate inference
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Rozita Dara
University of Guelph Canada
machine learning
data mining
deep learning
data analytics
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Eric Xing
Carnegie Mellon University United States of America
machine learning
data mining
statistical learning
probabilistic modeling
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Euijin Choo
University of Alberta Canada
machine learning
data mining
deep learning
big data analytics
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