Variational Inference Professors in Global

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Hina Shaheen
University of Manitoba Canada
bayesian inference
statistical machine learning
computational modelling
machine learning
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Xinran Li
University of Chicago United States of America
causal inference
randomization-based inference
bayesian inference
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Raaz Dwivedi
Cornell University Netherlands
causal inference
bayesian inference
statistical machine learning
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Abhishek Chakrabortty
Texas A&M University United States of America
statistical inference
causal inference
bayesian inference
machine learning
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Vanessa Mcnealis
University of Glasgow United Kingdom
causal inference
bayesian inference
hierarchical modelling
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Melike Alper
University of Southampton United Kingdom
variance estimation
empirical likelihood inference
design inference
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Aad Van Der Vaart
Delft University of Technology Netherlands
causal inference
statistical modeling
statistical analysis
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John Zito
Duke University Singapore
bayesian inference
vector autoregressions
stochastic volatility
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Jee-seon Kim
University of Wisconsin–Madison United States of America
causal inference
latent variable modeling
machine learning
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Ruohan Zhan
University College London United Kingdom
causal inference
statistical learning
machine learning
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Jonas Peters
ETH Zurich Switzerland
causal inference
statistical learning
machine learning
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Maurits Kaptein
Eindhoven University of Technology Belgium
causal inference
statistical learning
sequential experimentation
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Anish Agarwal
Columbia University United States of America
causal inference
machine learning
causal machine learning
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Guang Cheng
Purdue University United States of America
high dimensional statistical inferences
semi-nonparametric inferences
machine learning
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
statistical machine learning
causal machine learning
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Manfred Kronz
Friedrich-Alexander-Universität Erlangen-Nürnberg Germany
statistical modeling
predictive analytics
statistical analysis
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Danica Sutherland
University of British Columbia Canada
statistical machine learning
theoretical machine learning
machine learning
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David Scheinker
Stanford University United States of America
probabilistic modeling
statistical analysis
machine learning
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Eric Xing
Carnegie Mellon University United States of America
probabilistic modeling
statistical learning
machine learning
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Saber Salehkaleybar
Leiden University Netherlands
statistical modeling
predictive analytics
machine learning
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Minh Huynh
Monash University Australia
statistical modeling
predictive analytics
machine learning
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