Network Causal Inference Professors in Global

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Biwei Huang
University of California, San Diego United States of America
causal inference
automated causal discovery
machine learning
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Yonghan Jung
University of Illinois United States of America
causal inference
causal data science
machine learning
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Yixin Wang
University of Michigan United States of America
causal inference
probabilistic generative modeling
machine learning
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Samrachana Adhikari
New York University United States of America
causal inference
predictive modeling
machine learning
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Nathan Kallus
Cornell University Netherlands
causal inference
machine learning
network science
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Guang Cheng
Purdue University United States of America
high dimensional statistical inferences
semi-nonparametric inferences
machine learning
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John Oommen
Carleton University Canada
neural networks
pattern recognition
statistical pattern recognition
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Keith Jenkins
University of Southern California United States of America
neural networks
pattern recognition
machine learning
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D.m.j. Tax
Delft University of Technology Netherlands
neural networks
pattern recognition
machine learning
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Pascal Vincent
University of Montreal Canada
neural networks
pattern recognition
machine learning
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Nikolai Kühne
Aalborg University Denmark
neural networks
sequence modelling
machine learning
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Gerasimos Spanakis
Maastricht University Netherlands
neural networks
computational modeling
machine learning
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Jaime Ide
Yale University United States of America
pattern recognition
predictive modeling
machine learning
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Ioannis Paschalidis
Boston University United States of America
network optimization
predictive modeling
machine learning
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Roland Goecke
University of New South Wales Australia
pattern recognition
machine learning
computational behaviour analysis
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Sanjeev Kulkarni
Princeton University United States of America
statistical pattern recognition
machine learning
sensor networks
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Mohammed Abuibaid
Carleton University Canada
network optimization
machine learning
in-network processing
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Christopher Brinton
Purdue University United States of America
network optimization
machine learning
social learning networks
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Mahdi Khodayar
The University of Tulsa Iran
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statistical pattern recognition
machine learning
deep neural networks
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Carlo Fischione
KTH Royal Institute of Technology Sweden
machine learning
networked artificial intelligence
communication networks
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Konstantin Zuev
California Institute of Technology United States of America
network models
complex networks
network resilience
network science
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