Parameter Inference Professors in Global

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Zoltán Szabó
London School of Economics and Political Science United Kingdom
bayesian inference
shape-constrained prediction
statistical machine learning
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Hina Shaheen
University of Manitoba Canada
bayesian inference
machine learning
statistical machine learning
computational modelling
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Chunming Zhang
University of Wisconsin–Madison United States of America
large-scale simultaneous inference
machine learning
semi-parametric estimation
non-parametric estimation
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Karthikeyan Umapathy
Toronto Metropolitan University Canada
pattern classification
computational modeling
feature extraction
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Jethro Linley
University of Glasgow United Kingdom
predictive analytics
statistical machine learning
statistical modelling
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Xinran Li
University of Chicago United States of America
randomization-based inference
causal inference
bayesian inference
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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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Guang Cheng
Purdue University United States of America
semi-nonparametric inferences
high dimensional statistical inferences
machine learning
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Ricardo Baptista
California Institute of Technology United States of America
bayesian inference
probabilistic modeling
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Tony Cai
University of Pennsylvania United States of America
large-scale inference
statistical machine learning
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Vanessa Mcnealis
University of Glasgow United Kingdom
causal inference
bayesian inference
semi-parametric estimation
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Yian Ma
University of California, San Diego United States of America
bayesian inference algorithms
scalable inference methods
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Raaz Dwivedi
Cornell University Netherlands
causal inference
bayesian inference
statistical machine learning
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Nan Zou
Macquarie University Australia
statistical inference for dynamical systems
statistical inference for massive datasets
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Filippo Ascolani
Duke University Singapore
nonparametric inference
bayesian inference
statistical modeling
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James Norris
University of Cambridge United Kingdom
bayesian inference
statistical modeling
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Adji Dieng
Princeton University United States of America
probabilistic modeling
statistical machine learning
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
statistical machine learning
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Tom Rainforth
University of Oxford United Kingdom
approximate inference
probabilistic programming
statistical machine learning
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