Synthetic Data Calibration Professors in Global

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Hina Shaheen
University of Manitoba Canada
statistical machine learning
machine learning
data analysis
computational modelling
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George Moustakides
University of Patras Greece
statistical signal processing
machine learning
sequential detection
adaptive signal processing
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Mi Park
University of British Columbia Canada
synthetic data
statistical machine learning
theoretical machine learning
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Nipanjana Patra
University of Western Australia Australia
precision calibration
machine learning
deep learning
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Nediljko Budisa
University of Manitoba Canada
synthetic biology
synthetic metabolism
synthetic cells
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Yuchen Wu
Cornell University Netherlands
sampling algorithms
statistical machine learning
machine-generated data
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Xujie Si
University of Toronto Canada
synthesis
machine learning
deep learning
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Yuying Xie
Michigan State University United States of America
spatial data analysis
statistical machine learning
high dimensional data analysis
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Yisong Yue
California Institute of Technology United States of America
statistical machine learning
structured machine learning
machine learning
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Raman Arora
Johns Hopkins University United States of America
stochastic approximation algorithms
statistical signal processing
machine learning
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
machine learning
stochastic optimization
constrained optimization
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John Quilty
University of Waterloo Canada
machine learning
data assimilation
deep learning
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Ralf Peeters
Maastricht University Netherlands
machine learning
mathematical modelling
statistical parameter estimation
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Sahand Negahban
Yale University United States of America
statistical signal processing
machine learning
high-dimensional estimation
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Mårten Wadenbäck
Linköping University Sweden
robust feature matching
machine learning
deep learning
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Anders Bæk-petersen
University of Southern Denmark Denmark
machine learning
automated decision making
mathematical modelling
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Michael Alvarez
California Institute of Technology United States of America
machine learning
statistical computational modeling
deep learning
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Anna Choromanska
New York University Tandon School of Engineering United States of America
machine learning
large data analysis
deep learning
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Yoshua Bengio
University of Montreal Canada
machine learning
statistical learning algorithms
deep learning
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John Doe
University of Wisconsin–Madison United States of America
machine learning
data analysis
deep learning
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Yuxin Chen
Princeton University United States of America
statistical signal processing
machine learning
high-dimensional estimation
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