Learning Models Professors in Global

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Pascal Vincent
University of Montreal Canada
machine learning
statistical models
representation learning
deep learning
pattern recognition
neural networks
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Alexander Rakhlin
Massachusetts Institute of Technology United States of America
machine learning
large language models
statistical learning
neural networks
reinforcement learning
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Hossein Hassani
Toronto Metropolitan University Canada
machine learning
large language models
vision language models
deep learning
reinforcement learning
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Samir Maity
Aalborg University Denmark
language modeling
machine learning
deep learning
predictive modeling
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John Oommen
Carleton University Canada
learning systems
pattern recognition
stochastic learning
neural networks
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Fergus Nevill
New York University United States of America
machine learning
representation learning
generative models
deep learning
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Daniel Truhn
RWTH Aachen University Germany
machine learning
large language models
generative models
deep learning
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Martha White
University of Alberta Canada
machine learning
generative models
deep learning
neural networks
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Brokoslaw Laschowski
University of Toronto Canada
machine learning
deep learning
neural networks
reinforcement learning
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Gerasimos Spanakis
Maastricht University Netherlands
machine learning
deep learning
computational modeling
neural networks
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Honglak Lee
University of Michigan United States of America
machine learning
representation learning
deep learning
large-scale learning
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Shaon Shuvo
University of Windsor Canada
machine learning
modeling
deep learning
reinforcement learning
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Jason Lee
University of California, Berkeley United States of America
machine learning
representation learning
deep learning
reinforcement learning
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Maryam Fazel
University of Washington United States of America
machine learning
learning control
deep learning
reinforcement learning
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Ekta Vats
Uppsala University Sweden
machine learning
large language models
deep learning
vision-language models
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Nikolai Kühne
Aalborg University Denmark
machine learning
large language models
sequence modelling
neural networks
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Jason Lee
University of California, Berkeley United States of America
machine learning
representation learning
deep learning
reinforcement learning
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Jaime Ide
Yale University United States of America
machine learning
pattern recognition
theoretical modeling
predictive modeling
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Kai Brüssau
University of Hamburg Germany
classification models
regression models
large language models
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Alan Yuille
Johns Hopkins University United States of America
mathematical models
computational models
machine learning
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Kim Blackmore
Australian National University Australia
learning systems
machine learning
pattern recognition
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