Applied Bayesian Inference Professors in Global

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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian methods
efficient bayesian computation
approximate bayesian methods
bayesian graphical models
machine learning
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Yanan Fan
University of New South Wales Australia
bayesian inference
bayesian computation
approximate bayesian computation
bayesian nonparametrics
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Abhishek Chakrabortty
Texas A&M University United States of America
bayesian inference
statistical inference
machine learning
causal inference
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Guanyu Hu
Michigan State University United States of America
bayesian computation
bayesian nonparametric
big data inference
causal inference
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Sharmistha Guha
Texas A&M University United States of America
bayesian causal inference
bayesian high dimensional regression
bayesian object-oriented regression
bayesian nonparametric mixture models
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Mayank Chadha
University of California, San Diego United States of America
bayesian decision theory
bayesian optimization
applied mechanics
machine learning
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Rajesh Ranganath
New York University United States of America
probabilistic inference
statistical inference
machine learning
causal inference
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Theo Damoulas
University of Warwick United Kingdom
bayesian statistics
bayesian nonparametrics
probabilistic machine learning
approximate inference methodologies
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Sara Wade
University of Edinburgh United Kingdom
bayesian nonparametrics
variational inference
machine learning
map inference
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Mohammad Anam Khan
University of Toronto Canada
statistical inference
biostatistical analysis
machine learning
causal inference
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Trevor Campbell
University of British Columbia Canada
bayesian inference
bayesian theory
bayesian nonparametrics
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Edson Utazi
University of Southampton United Kingdom
bayesian inference
bayesian computation
machine learning
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Xinran Li
University of Chicago United States of America
bayesian inference
randomization-based inference
causal inference
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Jaehee Kim
Cornell University Netherlands
bayesian inference
statistical inference
machine learning
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Ricardo Silva
University College London United Kingdom
bayesian inference
relational inference
machine learning
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Ricardo Silva
University College London United Kingdom
bayesian inference
relational inference
machine learning
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Aaron Schein
University of Chicago United States of America
applied causal inference
bayesian statistics
machine learning
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Umberto Picchini
University of Gothenburg Sweden
approximate bayesian computation
bayesian computational methods
statistical inference
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David Taylor
Monash University Australia
bayesian inference
causal inference
applied economics
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Peter Mueller
University of Texas at Austin United States of America
nonparametric bayesian inference
bayesian bioinformatics
computational methods in bayesian inference
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Umberto Picchini
Chalmers University of Technology Sweden
approximate bayesian computation
bayesian computational methods
statistical inference
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