Reliable Generalization Professors in Global

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Rajesh Ranganath
New York University United States of America
generalization
interpretability
probabilistic inference
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Ying Jin
University of Pennsylvania United States of America
generalizability
selective inference
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Karthik Pattabiraman
University of British Columbia Canada
reliable computing systems
dependable software
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Rafi Muhanna
Georgia Institute of Technology United States of America
reliable engineering computing
structural reliability
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Samuel Cooper
University of Texas at Austin United States of America
higher-order generalization
stimulus generalization
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Min Qiu
University of New South Wales Australia
reliable communication networks
reliable storage systems
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Anastasios Magdalinos
University of Southampton United Kingdom
robust inference
predictive regressions
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George Candea
École Polytechnique Fédérale de Lausanne Switzerland
predictable performance
dependable systems
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Line Clemmensen
University of Copenhagen Denmark
trustworthy modeling
explainable modeling
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James Booth
Cornell University Netherlands
generalized linear models
exact inference
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Kevin Smith
Royal Institute of Technology Sweden
interpretability
generative modeling
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Marc Gendron-bellemare
University of Montreal Canada
probabilistic prediction
generative modeling
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Ludwig Schmidt
Stanford University United States of America
reliable generalization
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Henrik Mølbak Frederiksen
Aalborg University Denmark
reliable machine learning
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Mike Holenderski
Eindhoven University of Technology Belgium
reliable machine learning
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Cassio De Campos
Eindhoven University of Technology Belgium
reliable machine learning
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Sakshi Ghai
London School of Economics and Political Science United Kingdom
generalizability
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Jessica Lee
University of Sydney Australia
generalization
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Amy Zhang
University of Texas at Austin United States of America
generalization
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Hassan Sajjad
Dalhousie University Canada
generalization
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Samuel Cooper
University of Texas at Austin United States of America
generalization
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