Hierarchical Linear Models Professors in Global

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Debdeep Pati
University of Wisconsin–Madison United States of America
hierarchical modeling
machine learning
high dimensional network analysis
bayesian graphical models
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Alan Yuille
Johns Hopkins University United States of America
mathematical models
computational models
machine learning
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Nanwei Wang
University of New Brunswick Canada
linear mixed models
machine learning
graphical models
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Joakim Munkhammar
Uppsala University Sweden
mathematical modeling
machine learning
statistical modeling
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Kai Brüssau
University of Hamburg Germany
regression models
classification models
large language models
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Luke Miller
Radboud University Netherlands
computational modeling
machine learning
neural network modeling
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Eric Darve
Stanford University United States of America
numerical linear algebra
large-language models
machine learning
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Kamal Hossain
University of Melbourne Australia
computational modeling
machine learning
statistical modeling
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Jaime Ide
Yale University United States of America
theoretical modeling
machine learning
predictive modeling
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Tilda Herrgårdh
Linköping University Sweden
mathematical modelling
machine learning
mechanistic models
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Cemal Erdem
Umeå University Sweden
mathematical modeling
machine learning
large-scale mechanistic modelling
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Hina Shaheen
University of Manitoba Canada
computational modelling
machine learning
statistical machine learning
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Yang Feng
New York University United States of America
machine learning
statistical modeling
high-dimensional data analysis
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Wicher Bergsma
London School of Economics and Political Science United Kingdom
regression models
statistical modeling
graphical models
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Nikolai Kühne
Aalborg University Denmark
sequence modelling
machine learning
large language models
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Magnus Röding
Chalmers University of Technology Sweden
stochastic modeling
machine learning
statistical modeling
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Chunfang Lin
Queen's University Canada
machine learning
statistical modeling
simulation models
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Fangxin Fang
Imperial College London United Kingdom
machine learning
geophysical models
predictive modeling
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Bryon Aragam
University of Chicago Booth School of Business United States of America
deep generative models
probabilistic modeling
statistical machine learning
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning algorithms
machine learning theory
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