Empirical Likelihood Professors in Global

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Raaz Dwivedi
Cornell University Netherlands
causal inference
random sampling
bayesian inference
statistical machine learning
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Alastair Hall
University of Manchester United Kingdom
generalized empirical likelihood
statistical inference
indirect inference
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Matthew Jenssen
King's College London United Kingdom
probability
probabilistic
discrete probability
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Rajesh Ranganath
New York University United States of America
probabilistic inference
statistical inference
causal inference
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Stanislav Volgushev
University of Toronto Canada
empirical process theory
probability
theoretical statistics
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Miklos Racz
Northwestern University United States of America
probability
discrete probability
applied probability
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Miklos Racz
Northwestern University United States of America
probability
discrete probability
applied probability
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Syed Haider
Columbia University United States of America
probability
causal inference
predictive modeling
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Torkel Erhardsson
Linköping University Sweden
statistical inference
probability theory
bayesian inference
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Wei Zhang
University of Sydney Australia
likelihood approximation
probability density estimation
statistical modelling
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Toru Kitagawa
Brown University United States of America
empirical macroeconomics
causal inference
experimental economics
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Abhishek Chakrabortty
Texas A&M University United States of America
statistical inference
causal inference
bayesian inference
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Tao Ma
University of Southern California United States of America
probability
statistical
predictive analytics
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Wenlong Mou
University of Toronto Canada
probability
applied probability
theoretical statistics
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Xinran Li
University of Chicago United States of America
causal inference
randomization-based inference
bayesian inference
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Anthony Pakes
University of Western Australia Australia
probability theory
applied probability
statistical distributions
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Tatjana Pavlenko
Uppsala University Sweden
statistical inference
applied probability
statistical machine learning
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Ben Hansen
University of Michigan United States of America
causal inference
observational studies
randomized studies
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Tom Rainforth
University of Oxford United Kingdom
approximate inference
probabilistic programming
statistical machine learning
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Siyu Heng
New York University United States of America
causal inference
observational studies
randomized trials
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Hina Shaheen
University of Manitoba Canada
bayesian inference
probability stochastic processes
statistical machine learning
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