Interpretable Probabilistic Machine Learning Professors in Global

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Flora Salim
University of New South Wales Australia
trustworthy machine learning
robust machine learning
multimodal machine learning
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Michael Guerzhoy
University of Toronto Canada
interpretable machine learning
mechanistic interpretability
machine learning
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Berk Gorgulu
McMaster University Canada
interpretable machine learning
predictive analytics
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Guang Lin
Purdue University United States of America
interpretable ai
predictive modeling
statistical machine learning
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Rajesh Ranganath
New York University United States of America
probabilistic inference
interpretability
machine learning
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Alexandre Bouchard-côté
University of British Columbia Canada
probabilistic modelling
statistical machine learning
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Adji Dieng
Princeton University United States of America
probabilistic modeling
statistical machine learning
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
statistical machine learning
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Uta Noppeney
Radboud University Netherlands
probabilistic computations
perceptual inference
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Christoffer Back
University of Copenhagen Denmark
probabilistic inference
machine learning
computability learning theory
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Mikhail Glazunov
Delft University of Technology Netherlands
probabilistic modeling
explainability in ai
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Djordje Bajić
Delft University of Technology Netherlands
predictive understanding
computational modeling
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Xiaochen Yang
University of Glasgow United Kingdom
interpretability
statistical machine learning
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Tom Rainforth
University of Oxford United Kingdom
probabilistic programming
statistical machine learning
approximate inference
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Nikolay Malkin
University of Edinburgh United Kingdom
probabilistic reasoning
machine reasoning
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Michele Caprio
University of Manchester United Kingdom
imprecise probabilistic machine learning
machine learning
applied probability
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Mi Park
University of British Columbia Canada
theoretical machine learning
statistical machine learning
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Danica Sutherland
University of British Columbia Canada
theoretical machine learning
statistical machine learning
machine learning
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Madlene Nussbaum
Utrecht University Netherlands
predictive mapping
statistical machine learning
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David Inouye
Purdue University United States of America
trustworthy machine learning
robust machine learning
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Guotao Ma
University of Warwick United Kingdom
probabilistic analysis
machine learning
computational modeling
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