Scalable Deep Learning Professors in Global

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Steven Reece
University of Oxford United Kingdom
scalable human-agent computation
interpretable machine learning
machine learning
bayesian deep learning
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Nicolas Loizou
Johns Hopkins University United States of America
deep learning
distributed decentralized algorithms
machine learning
large-scale optimization
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
machine learning
bayesian deep learning
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
machine learning
bayesian deep learning
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Vladimir Vlassov
KTH Royal Institute of Technology Sweden
scalable deep learning
machine learning
large-scale distributed systems
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Pranav Bapat
Maastricht University Netherlands
scalable ai architectures
deep learning
machine learning
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Saikat Chatterjee
Royal Institute of Technology Sweden
deep learning
explainable machine learning
statistical machine learning
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Jingmin Huang
University of Southampton United Kingdom
deep learning
deep generative models
machine learning
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Yee Teh
University of Oxford United Kingdom
deep learning
large scale machine learning
machine learning
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Mehrdad Mahdavi
Pennsylvania State University United States of America
deep learning
large-scale machine learning
distributed optimization
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Pan Li
Georgia Institute of Technology United States of America
scalable analysis tools
geometric deep learning
machine learning
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Krishna Swamy
Yale University United States of America
deep learning
geometric deep learning
machine learning
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Naveed Akhtar
University of Western Australia Australia
deep learning
explainable artificial intelligence
machine learning
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Tingting Zhu
University of Oxford United Kingdom
deep learning
dynamic modelling
machine learning
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Saeed Anwar
University of Western Australia Australia
deep learning
explainable artificial intelligence
machine learning
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Honglak Lee
University of Michigan United States of America
deep learning
large-scale learning
machine learning
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Hon Kwan
University of Windsor Canada
deep learning
deep neural network design
machine learning
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Kin-choong Yow
University of Regina Canada
deep learning
deep reinforcement learning
machine learning
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Hongpeng Zhou
University of Manchester United Kingdom
deep learning
interpretable learning
machine learning
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Anna Choromanska
New York University Tandon School of Engineering United States of America
deep learning
machine learning
large data analysis
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Sun-yuan Kung
Princeton University United States of America
deep learning
explainable ai
machine learning
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