Interpretability In Machine Learning Professors in Global

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Michael Guerzhoy
University of Toronto Canada
interpretable machine learning
mechanistic interpretability
machine learning
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Fei Wang
Cornell University Netherlands
model interpretability
explainability
machine learning
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Fei Wang
Cornell University Netherlands
model interpretability
explainability
machine learning
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Matthias Wilms
University of Michigan United States of America
interpretability
explainability
machine learning
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Bahareh Tolooshams
University of Alberta Canada
interpretability
machine learning
representation learning
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Saikat Chatterjee
Royal Institute of Technology Sweden
explainable machine learning
data inference
statistical machine learning
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Henrik Boström
KTH Royal Institute of Technology Sweden
explainable machine learning
trustworthy machine learning
probabilistic machine learning
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Yingzhen Li
Imperial College London United Kingdom
explainable machine learning
machine learning
probabilistic machine learning
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Klaus-robert Müller
Technical University of Berlin Germany
explainable ai
machine learning
probabilistic machine learning
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Klaus Müller
Technical University of Berlin Germany
explainable ai
machine learning
probabilistic machine learning
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning theory
machine learning algorithms
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Danica Sutherland
University of British Columbia Canada
machine learning
theoretical machine learning
statistical machine learning
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Samy Bengio
École Polytechnique Fédérale de Lausanne Switzerland
machine learning
statistical machine learning
representation learning
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Arman Cohan
Yale University United States of America
machine learning
representation learning
language modeling
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Shai Ben-david
University of Waterloo Canada
interpretability in machine learning
reliability in machine learning
machine learning
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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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Alejandro Hernandez
Stockholm University Sweden
machine learning interpretability
applied machine learning
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Yunyao Cheng
Aalborg University Denmark
neural network interpretability
machine learning
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Pascal Germain
Laval University Canada
interpretable machine learning
machine learning
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Steven Reece
University of Oxford United Kingdom
interpretable machine learning
machine learning
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