Probabilistic Choice Models Professors in Global

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Chunfang Lin
Queen's University Canada
simulation models
statistical modeling
machine learning
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Joakim Munkhammar
Uppsala University Sweden
mathematical modeling
statistical modeling
machine learning
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Maximilian Kasy
University of Oxford United Kingdom
algorithmic decision making
machine learning
statistical decision theory
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Matthew Hole
Australian National University Australia
bayesian inference
mathematical modelling
stochastic systems
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Danielle Barth
Australian National University Australia
language probabilistic system
statistical modelling
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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Victor Panaretos
École Polytechnique Fédérale de Lausanne Switzerland
regression modeling
probability theory
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Crystal Linkletter
Brown University United States of America
bayesian hierarchical modeling
statistical modeling
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Ferenc Huszár
University of Cambridge United Kingdom
mathematical models
probabilistic foundations
machine learning
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Dun Fu
University College London United Kingdom
clinical prediction models
machine learning
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Debmalya Mandal
University of Warwick United Kingdom
computational social choice
machine learning
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Gökçin Çınar
University of Michigan United States of America
probabilistic design
machine learning
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Madhuchhanda Bhattacharjee
University of Manchester United Kingdom
regression modeling
bayesian integrated modeling
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John Witte
Stanford University United States of America
bayesian hierarchical modeling
machine learning
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Huajie Zhang
University of New Brunswick Canada
graphical probabilistic models
machine learning
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Fredrik Lindsten
Linköping University Sweden
statistical predictions
machine learning
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Egil Fischer
Utrecht University Netherlands
simulation models
mathematical modeling
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Tom York
Imperial College London United Kingdom
algorithmic decision-making
machine learning
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Lydia Liu
Princeton University United States of America
algorithmic decision-making
machine learning
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Bruno Gächter
ZHAW Zurich University of Applied Sciences Switzerland
predictive modeling
algorithmic decision-making
machine learning
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