Semiparametric Inference Professors in Global

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Vanessa Mcnealis
University of Glasgow United Kingdom
semi-parametric estimation
causal inference
bayesian inference
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Chunming Zhang
University of Wisconsin–Madison United States of America
semi-parametric estimation
large-scale simultaneous inference
non-parametric estimation
machine learning
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Xinran Li
University of Chicago United States of America
randomization-based inference
causal inference
bayesian inference
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Raaz Dwivedi
Cornell University Netherlands
causal inference
bayesian inference
statistical machine learning
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Rui Pires Da Silva Castro
Eindhoven University of Technology Belgium
network inference
pattern recognition
non-parametric high-dimensional statistics
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Zoltán Szabó
London School of Economics and Political Science United Kingdom
bayesian inference
statistical machine learning
shape-constrained prediction
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Marie Skov Breum
University of Copenhagen Denmark
semiparametric inference
causal inference
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Daniel Malinsky
Columbia University United States of America
semiparametric inference
causal inference
machine learning
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Raymond Wong
Texas A&M University United States of America
semi-parametric modeling
nonparametric modeling
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Jesper Sørensen
University of Copenhagen Denmark
semiparametric high-dimensional estimation
specification tests for semiparametric models
nonparametric identification
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Zhonghua Liu
Columbia University United States of America
semiparametric efficiency theory
causal inference
machine learning
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Howell Tong
London School of Economics and Political Science United Kingdom
semi-parametric approaches
likelihood-free inference
parametric methods
non-parametric methods
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Rajesh Ranganath
New York University United States of America
statistical inference
probabilistic inference
causal inference
machine learning
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Ashis Gangopadhyay
Boston University United States of America
semiparametric volatility estimation
nonparametric time series prediction
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Sara Wade
University of Edinburgh United Kingdom
map inference
variational inference
bayesian nonparametrics
machine learning
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Eduard Belitser
Vrije Universiteit Amsterdam Netherlands
nonparametric bayesian inference
high-dimensional inference
non-parametric estimation
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Sujin Wang
Texas A&M University United States of America
biostatistical inference
non-parametric methodology
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Kolyan Ray
Imperial College London United Kingdom
causal inference
variational inference
bayesian nonparametrics
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Daniela Golinelli
University of Pennsylvania United States of America
causal inference
statistical inference procedures
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Saikat Chatterjee
Royal Institute of Technology Sweden
data 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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