Bayesian Statistical Inference Professors in Global

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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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James Beck
California Institute of Technology United States of America
computational bayesian statistics
bayesian updating
stochastic system modeling
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Guang Cheng
Purdue University United States of America
high dimensional statistical inferences
machine learning
semi-nonparametric inferences
modern bayesian bootstrap methods
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Eric Xing
Carnegie Mellon University United States of America
machine learning
probabilistic modeling
statistical learning
data mining
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Nathan Kallus
Cornell University Netherlands
machine learning
causal inference
stochastic optimization
data mining
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Valen Johnson
Texas A&M University United States of America
bayesian variable selection
bayesian hypothesis testing
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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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Paulo Serra
Vrije Universiteit Amsterdam Netherlands
bayesian non-parametrics
empirical bayes
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Xinran Li
University of Chicago United States of America
bayesian inference
randomization-based inference
causal inference
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Dabao Zhang
Purdue University United States of America
statistical inference
bayesian
machine learning
data mining
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Ying Jin
University of Pennsylvania United States of America
selective inference
causal inference
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Shuangning Li
University of Chicago Booth School of Business United States of America
selective inference
causal inference
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Christina Lee Yu
Cornell University Netherlands
inference networks
causal inference
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Christina Kendziorski
University of Wisconsin–Madison United States of America
bayes methods
empirical bayes methods
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Daniel Xiang
University of Chicago United States of America
selective inference
empirical bayes methodology
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Christina Lee Yu
Cornell University Netherlands
inference networks
network causal inference
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Christina Yu
Cornell University Netherlands
inference networks
network causal inference
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Christina Yu
Cornell University Netherlands
inference networks
network causal inference
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Nikolaos Ignatiadis
University of Chicago United States of America
empirical bayes analysis
causal inference
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Garvesh Raskutti
University of Wisconsin–Madison United States of America
large-scale inference
theoretical statistics
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Pietro Ortoleva
Princeton University United States of America
non-bayesian decision-making
stochastic choice
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