Neural Model Interpretability Professors in Global

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Ludmila Stern
University of New South Wales Australia
interpreted communication
courtroom interpreting
legal interpreting
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Fei Wang
Cornell University Netherlands
model interpretability
explainability
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Fei Wang
Cornell University Netherlands
model interpretability
explainability
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Michael Guerzhoy
University of Toronto Canada
mechanistic interpretability
interpretable machine learning
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Matthias Wilms
University of Michigan United States of America
interpretability
explainability
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Xin Tang
University of British Columbia Canada
ai interpretability
ai explainability
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Yan Leng
University of Texas at Austin United States of America
interpretable machine learning
human-centric interpretability
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Amir Rahnama
KTH Royal Institute of Technology Sweden
interpretable machine learning
explainable machine learning
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Zihuai University
Stanford University United States of America
interpretable machine learning
explainable machine learning
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Helle Dam
Aarhus University Denmark
interpretation theory
consecutive interpreting
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Ehsan Mobaraki
Aalborg University Denmark
explainability
explainable artificial intelligence
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Anna Korhonen
University of Cambridge United Kingdom
explainability
cognitive modeling
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Tanya Titchkosky
University of Toronto Canada
interpretive sociology
interpretive methods
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Erica Thompson
University College London United Kingdom
model evaluation
inference models
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Luke Miller
Radboud University Netherlands
neural network modeling
neural computations
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Sandra Hale
University of New South Wales Australia
court interpreting
legal interpreting
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Arthur Lee
Boston University United States of America
neural predictions
neural patterns
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Jim Davies
Carleton University Canada
brain modeling
cognitive modeling
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Antje Weisheimer
University of Oxford United Kingdom
model uncertainty
predictability
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Arianna Bisazza
University of Groningen Netherlands
neural model interpretability
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Yunyao Cheng
Aalborg University Denmark
neural network interpretability
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