Machine Learning In Physics Professors in Global

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Victor Flambaum
University of New South Wales Australia
theoretical physics
quantum mechanics
particle physics
nuclear physics
atomic physics
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Gordon Watts
University of Washington United States of America
machine learning
computational physics
particle physics
nuclear physics
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Somnath Ghosh
Johns Hopkins University United States of America
multi-physics modeling
machine learning
computational mechanics
physics
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Tal Kachman
Radboud University Netherlands
machine learning
statistical physics
reinforcement learning
deep learning
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Jeffrey Schenker
Michigan State University United States of America
mathematical physics
theoretical physics
statistical physics
quantum mechanics
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Jason Lee
University of California, Berkeley United States of America
machine learning
reinforcement learning
deep learning
representation learning
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Jason Lee
University of California, Berkeley United States of America
machine learning
reinforcement learning
deep learning
representation learning
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Duncan O'dell
McMaster University Canada
mathematical physics
quantum physics
molecular physics
atomic physics
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Federico Bocci
Radboud University Netherlands
machine learning
biophysical modeling
mathematical modeling
deep learning
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Honglak Lee
University of Michigan United States of America
machine learning
deep learning
representation learning
large-scale learning
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Ferenc Huszár
University of Cambridge United Kingdom
machine learning
deep learning
bayesian machine learning
representation learning
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Charles Hoyle
University of Washington United States of America
theoretical physics
experimental physics
quantum mechanics
particle physics
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Simone Loreti
University of Bern Switzerland
computational physics
mathematical modelling
engineering physics
physics
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Phiala Shanahan
Massachusetts Institute of Technology United States of America
machine learning in physics
particle physics
nuclear physics
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning algorithms
machine learning theory
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Vinay Gogineni
University of Southern Denmark Denmark
quantum machine learning
machine learning
physics-informed neural networks
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Ambuj Tewari
University of Michigan United States of America
theory of machine learning
machine learning
reinforcement learning
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Yuxin Chen
University of Pennsylvania United States of America
machine learning theory
statistical machine learning
reinforcement learning
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Girish Chowdhary
University of Illinois United States of America
machine learning
machine vision
reinforcement learning
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Rudolf Römer
University of Warwick United Kingdom
mathematical physics
computational physics
biological physics
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David Brückner
University of Basel Switzerland
machine learning
theoretical physics
statistical physics
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