Generalized Regression Professors in Global

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Rajesh Ranganath
New York University United States of America
generalization
machine learning
probabilistic inference
deep generative modeling
statistical inference
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Pascal Vincent
University of Montreal Canada
machine learning
neural networks
deep learning
statistical models
pattern recognition
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Ferenc Huszár
University of Cambridge United Kingdom
generalization
machine learning
deep learning
bayesian machine learning
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Yee Teh
University of Oxford United Kingdom
large scale machine learning
machine learning
deep learning
probabilistic learning
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Molei Tao
Georgia Institute of Technology United States of America
generative modeling
machine learning
probabilistic machine learning
deep learning theory
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A.c.c. Coolen
Radboud University Netherlands
machine learning
neural networks
predictive analysis
statistical inference
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Kin-choong Yow
University of Regina Canada
machine learning
artificial general intelligence
deep learning
pattern recognition
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Gerasimos Spanakis
Maastricht University Netherlands
machine learning
neural networks
deep learning
computational modeling
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Martha White
University of Alberta Canada
machine learning
generative models
neural networks
deep learning
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Jaime Ide
Yale University United States of America
predictive modeling
machine learning
theoretical modeling
pattern recognition
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Hina Shaheen
University of Manitoba Canada
machine learning
statistical machine learning
computational modelling
bayesian inference
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Nicolas Le Roux
University of Montreal Canada
machine learning
neural networks
statistical modeling
deep learning
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Tim Rudner
University of Toronto Canada
machine learning
generative models
deep learning
bayesian inference
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George Azzopardi
University of Groningen Netherlands
machine learning
deep learning
predictive analysis
pattern recognition
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Laurent Charlin
Université de Montréal Canada
machine learning
deep learning
bayesian inference
statistical models
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Mingyuan Zhou
University of Texas at Austin United States of America
generative models
probabilistic machine learning
deep neural networks
bayesian analysis
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John Oommen
Carleton University Canada
neural networks
stochastic learning
statistical pattern recognition
pattern recognition
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James Booth
Cornell University Netherlands
generalized linear models
machine learning
bayesian analysis
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Sylvain Sardy
University of Geneva Switzerland
regression
predictive modeling
machine learning
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Ferenc Huszár
University of Cambridge United Kingdom
generalization
machine learning
deep learning
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Matias Carrasco Kind
University of Illinois United States of America
generative predictive models
machine learning
deep learning
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