Generative Models Professors in Global

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Nicolai Rothe
Technical University of Berlin Germany
generative ai
statistical modeling
mathematical modeling
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William Seaman
Duke University Singapore
generative computational tools
generative poetic systems
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Minshuo Chen
Northwestern University United States of America
generative ai
data modeling
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Volodymyr Kuleshov
Cornell University Netherlands
generative probabilistic methods
diffusion-based generative algorithms
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Juliette Arevalo
Delft University of Technology Netherlands
collaborative modelling
participatory modelling
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Hedderik Van Rijn
University of Groningen Netherlands
generative ai education
computational modeling
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Edwin Kolbe
University of Basel Switzerland
microscopic models
statistical model
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Mikael Hedlind
KTH Royal Institute of Technology Sweden
data models
model driven engineering
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Nadiya Kostyuk
Carnegie Mellon University United States of America
computational modeling
mathematical modeling
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Justin Remais
University of California, Berkeley United States of America
computational modeling
mathematical modeling
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Wim Van Drongelen
University of Chicago United States of America
computational modeling
mathematical modeling
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Anmar Khadra
McGill University Canada
computational modeling
mathematical modeling
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Etiënne Rouwette
Radboud University Netherlands
group model building
facilitated modeling
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Trey Ideker
University of California, San Diego United States of America
computational modeling
genetic networks
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Daniel Segrè
Boston University United States of America
mathematical modeling
genetic networks
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Jeff Boisvert
University of Alberta Canada
geostatistical modeling
numerical modeling
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Hojae Yi
Pennsylvania State University United States of America
mathematical modeling
numerical modeling
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Eric Darve
Stanford University United States of America
large-language models
transformer models
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Bryon Aragam
University of Chicago Booth School of Business United States of America
deep generative models
probabilistic modeling
latent variable models
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Daniel Graham
Imperial College London United Kingdom
statistical modelling
mathematical modelling
economic modelling
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Ken Beath
Macquarie University Australia
mixture models
latent variable models
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