Deep Learning Methods Professors in Global

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John Anderson
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
behavioral methods
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
machine learning
deep probabilistic ai
bayesian deep learning
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Federico Bocci
Radboud University Netherlands
deep learning
computational methods
machine learning
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Jingmin Huang
University of Southampton United Kingdom
deep learning
deep generative models
machine learning
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Ruqi Zhang
Purdue University United States of America
deep learning
probabilistic methods
machine learning
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Kin-choong Yow
University of Regina Canada
deep learning
deep reinforcement learning
machine learning
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Mohammad Yazdani-asrami
University of Glasgow United Kingdom
deep learning
big data techniques
machine learning
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Krishna Swamy
Yale University United States of America
deep learning
machine learning
geometric deep learning
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Molei Tao
Georgia Institute of Technology United States of America
deep learning theory
machine learning
geometric methods
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Yee Teh
University of Oxford United Kingdom
deep learning
machine learning
large scale machine learning
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Amos Storkey
University of Edinburgh United Kingdom
deep learning
machine learning
bayesian methods
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Anand Joshi
University of Southern California United States of America
deep learning
machine learning
geometric methods
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Ben Adcock
Simon Fraser University Canada
deep learning
machine learning
numerical methods
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Dale Durran
University of Washington United States of America
deep learning
machine learning
numerical methods
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Dave Touretzky
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
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Robert Gracie
University of Waterloo Canada
deep learning
machine learning
numerical methods
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Caleb Pomeroy
University of Toronto Canada
computational methods
statistical methods
experimental methods
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Eli Ben-michael
Carnegie Mellon University United States of America
computational methods
statistical methods
machine learning
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Ingemar André
Lund University Sweden
computational methods
high-throughput methods
experimental methods
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Samir Maity
Aalborg University Denmark
deep learning
machine learning
computational approaches
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Hon Kwan
University of Windsor Canada
deep learning
machine learning
deep neural network design
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