Stochastic Neural Models Professors in Global

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Luke Miller
Radboud University Netherlands
neural network modeling
computational modeling
neural computations
machine learning
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Frederi Viens
Michigan State University United States of America
stochastic control
stochastic volatility
nonlinear stochastic filtering
stochastic pdes
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Joris Mooij
University of Amsterdam Netherlands
computational models
statistical learning
machine learning
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Khader Khadraoui
Laval University Canada
stochastic processes
stochastic differential equations
high-dimensional probabilistic models
statistical theory modeling
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Eric Xing
Carnegie Mellon University United States of America
statistical learning
probabilistic modeling
machine learning
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Hina Shaheen
University of Manitoba Canada
statistical machine learning
probability stochastic processes
computational modelling
machine learning
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Prasenjit Ghosh
Texas A&M University United States of America
statistical learning
bayesian modeling
machine learning
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Laurence Frank
Utrecht University Netherlands
statistical learning
predictive modelling
machine learning
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Titouan Muzellec
University of Vienna Austria
statistical learning
predictive modeling
machine learning
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Guang Lin
Purdue University United States of America
statistical learning
predictive modeling
machine learning
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Vidvuds Ozolins
Yale University United States of America
computational modeling
statistical simulation
machine learning
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Andre Amaral
University of Southampton United Kingdom
bayesian modelling
spatio-temporal statistical modelling
machine learning
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
machine learning
hierarchical modeling
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Mahdi Khodayar
The University of Tulsa Iran
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deep neural networks
statistical pattern recognition
machine learning
probabilistic graphical models
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Sueyeon Chung
Harvard University United States of America
artificial neural networks
machine learning
neural computation
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Jaime Ide
Yale University United States of America
predictive modeling
machine learning
theoretical modeling
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Yee Teh
University of Oxford United Kingdom
large scale machine learning
machine learning
probabilistic learning
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Peter Mccullagh
University of Chicago United States of America
stochastic processes
spatial models
structured covariance models
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Xenia Miscouridou
Imperial College London United Kingdom
stochastic process modeling
statistical network modeling
bayesian statistical machine learning
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Mircea Grigoriu
Cornell University Netherlands
stochastic calculus
stochastic differential equations
stochastic partial differential equations
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Mahdieh Arezoomandan
University of Geneva Switzerland
stochastic differential equations
stochastic partial differential equations
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