Bayesian Simulations Professors in Global

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Magnus Röding
Chalmers University of Technology Sweden
simulation
stochastic modeling
machine learning
statistical modeling
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Charbel Farhat
Stanford University United States of America
bayesian optimization
mathematical models
probabilistic machine learning
computational algorithms
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Stijn De Vuyst
Ghent University Belgium
simulation
stochastic modeling
stochastic optimization
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Edward Cripps
University of Western Australia Australia
bayesian longitudinal analysis
probabilistic modeling
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Prasanth Nair
University of Toronto Institute for Aerospace Studies Canada
bayesian model calibration
computational modeling
machine learning
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Wentao Li
University of Manchester United Kingdom
bayesian computation methods
bayesian asymptotic theory
simulation-based inference
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Wentao Li
University of Manchester United Kingdom
bayesian computation methods
bayesian asymptotic theory
simulation-based inference
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Shijie Deng
Georgia Institute of Technology United States of America
simulation
stochastic modeling
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Yaren Kaya
Columbia University United States of America
simulation
stochastic modeling
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Kaizheng Wang
Columbia University United States of America
simulation
stochastic modeling
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Peter Glynn
Stanford University United States of America
simulation
stochastic modeling
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Mathisca De Gunst
Vrije Universiteit Amsterdam Netherlands
mathematical models
stochastic modeling
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Muhammad Akram
Pennsylvania State University United States of America
simulation
computational modeling
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Javanshir Fouladvand
Utrecht University Netherlands
simulation
computational modeling
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Oluwatoyin Adeleke
Dalhousie University Canada
simulation
computational modeling
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Christian Frier
Aalborg University Denmark
probabilistic modeling
stochastic modeling
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Professor
Stanford University United States of America
stochastic modeling
computational modeling
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Sergei Dudarev
University of Oxford United Kingdom
mathematical models
stochastic models
high-performance computing simulations
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Thomas Ouldridge
Imperial College London United Kingdom
simulation
theoretical 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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