Equivariant Representation Learning Professors in Global

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Nicholas Rhinehart
University of Toronto Canada
imitation learning
reinforcement learning
robot learning
machine learning
deep learning
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Yuhong Guo
Carleton University Canada
representation learning
self-supervised learning
reinforcement learning
semi-supervised learning
machine learning
weakly supervised learning
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Yuhong Guo
Carleton University Canada
representation learning
self-supervised learning
reinforcement learning
semi-supervised learning
machine learning
weakly supervised learning
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Jason Lee
University of California, Berkeley United States of America
representation learning
reinforcement learning
machine learning
deep learning
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Jason Lee
University of California, Berkeley United States of America
representation learning
reinforcement learning
machine learning
deep learning
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Florian Shkurti
University of Toronto Canada
imitation learning
reinforcement learning
machine learning
inverse reinforcement learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
reinforcement learning
robot learning
deep learning
deep reinforcement learning
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Pascal Poupart
University of Waterloo Canada
self-supervised learning
reinforcement learning
machine learning
causal learning
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Tess Smidt
Massachusetts Institute of Technology United States of America
representation learning
symmetry equivariant neural networks
machine learning
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Guilherme Dinis Chaliane Junior
Stockholm University Sweden
representation learning
reinforcement learning
machine learning
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Dhruv Shah
Princeton University United States of America
representation learning
reinforcement learning
machine learning
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Sarthak Yadav
Aalborg University Denmark
representation learning
self-supervised learning
deep learning
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Randall Balestriero
Brown University United States of America
representation learning
self-supervised learning
deep learning
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Linus Ericsson
University of Glasgow United Kingdom
representation learning
machine learning
multi-modal learning
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Ferenc Huszár
University of Cambridge United Kingdom
representation learning
machine learning
deep learning
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Atsuto Maki
KTH Royal Institute of Technology Sweden
representation learning
machine learning
deep learning
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Samy Bengio
École Polytechnique Fédérale de Lausanne Switzerland
representation learning
machine learning
deep learning
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Tian Liang
University of Manchester United Kingdom
representation learning
machine learning
deep learning
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Mirco Ravanelli
Concordia University Canada
representation learning
machine learning
deep learning
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Sirisha Rambhatla
University of Waterloo Canada
representation learning
machine learning
deep learning
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Pascal Vincent
University of Montreal Canada
representation learning
machine learning
deep learning
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