Random Matrix Models Professors in Global

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Robin Evans
University of Oxford United Kingdom
latent variable models
marginal models
multivariate statistical models
bayesian network models
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Gennady Samorodnitsky
Cornell University Netherlands
stochastic modeling
random fields
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Stanford University United States of America
stochastic modeling
computational modeling
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Yuqi Gu
Columbia University United States of America
deep generative models
latent variable models
probabilistic graphical models
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
deep generative models
latent variable models
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Camila De Souza
Western University Canada
mixed effect models
hierarchical mixture models
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Paul Mcnicholas
McMaster University Canada
matrix variate distributions
machine learning
pattern recognition
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Magnus Röding
Chalmers University of Technology Sweden
stochastic modeling
machine learning
statistical modeling
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Ziyang Lyu
University of New South Wales Australia
mixed models
machine learning
pattern recognition
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Eva Cantoni
University of Geneva Switzerland
mixed models
variable model selection
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Fangxin Fang
Imperial College London United Kingdom
machine learning
model reduction
predictive modeling
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Jonathan Pillow
Princeton University United States of America
neural encoding models
latent variable models
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Alan Welsh
Australian National University Australia
mixed models
statistical modelling
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Reimer Kühn
King's College London United Kingdom
random matrices
risk modeling
neural networks
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Edwin Kolbe
University of Basel Switzerland
microscopic models
statistical model
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Mingyuan Zhou
University of Texas at Austin United States of America
generative models
probabilistic machine learning
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Kamal Hossain
University of Melbourne Australia
machine learning
computational modeling
statistical modeling
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Jan Ambjørn
University of Copenhagen Denmark
matrix models
random paths
random surfaces
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Imad Jaimoukha
Imperial College London United Kingdom
model reduction
model predictive control
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Jaime Ide
Yale University United States of America
machine learning
predictive modeling
pattern recognition
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Mateus Maia Marques
University of Glasgow United Kingdom
statistical learning models
bayesian tree models
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