Bayesian Deep Learning Professors in Global

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Yee Teh
University of Oxford United Kingdom
deep learning
bayesian statistics
machine learning
bayesian nonparametrics
large scale machine learning
probabilistic learning
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
bayesian methods
efficient bayesian computation
machine learning
approximate bayesian methods
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Gerasimos Spanakis
Maastricht University Netherlands
deep learning
machine learning
computational modeling
neural networks
data mining
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Yanan Fan
University of New South Wales Australia
bayesian computation
bayesian inference
approximate bayesian computation
bayesian nonparametrics
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Yarin Gal
University of Oxford United Kingdom
bayesian deep learning
deep probabilistic ai
machine learning
deep reinforcement learning
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Xenia Miscouridou
Imperial College London United Kingdom
bayesian statistical machine learning
deep learning
bayesian nonparametrics
deep generative models
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Sharmistha Guha
Texas A&M University United States of America
bayesian high dimensional regression
bayesian object-oriented regression
bayesian causal inference
bayesian nonparametric mixture models
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Qifan Song
Purdue University United States of America
bayesian data science
deep learning
machine learning
massive data modeling
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Hina Shaheen
University of Manitoba Canada
bayesian inference
machine learning
statistical machine learning
computational modelling
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Peter Mueller
University of Texas at Austin United States of America
bayesian bioinformatics
nonparametric bayesian inference
computational methods in bayesian inference
bayesian adaptive clinical trial design
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Mogana Ganggayah
Monash University Australia
deep learning
machine learning
predictive modeling
data mining
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Tahereh Koohi
University of New South Wales Australia
deep learning
machine learning
neural networks
evolutionary algorithms
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Irina Rish
University of Montreal Canada
deep learning
machine learning
probabilistic inference
biologically plausible reinforcement learning
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Mehrdad Mahdavi
Pennsylvania State University United States of America
deep learning
large-scale machine learning
computational statistical machine learning
computational learning theory
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Dabao Zhang
Purdue University United States of America
bayesian
machine learning
data mining
massive data modeling
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Edson Utazi
University of Southampton United Kingdom
bayesian computation
bayesian inference
machine learning
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Mikhail Glazunov
Delft University of Technology Netherlands
bayesian deep learning
deep learning
probabilistic modeling
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Ferenc Huszár
University of Cambridge United Kingdom
bayesian machine learning
deep learning
machine learning
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Trevor Campbell
University of British Columbia Canada
bayesian inference
bayesian theory
bayesian nonparametrics
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Jeremias Knoblauch
University College London United Kingdom
bayesian inference
deep learning
bayesian methods
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Chris Maddison
University of Toronto Canada
bayesian inference
deep learning
machine learning
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