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