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Bayesian Graph Structure Learning
Bayesian Graph Structure Learning Professors in Global
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Professor
Yanan Fan
University of New South Wales
Australia
bayesian computation
bayesian inference
bayesian nonparametrics
approximate bayesian computation
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Professor
Edson Utazi
University of Southampton
United Kingdom
bayesian computation
bayesian inference
machine learning
spatiotemporal modeling
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Professor
Alexander Hartemink
Duke University
Singapore
bayesian networks
bayesian statistics
machine learning
graphical models
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Professor
Paul Arora
University of Toronto
Canada
bayesian networks
bayesian statistics
machine learning
graphical models
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Professor
Thomas Nielsen
Aalborg University
Denmark
bayesian networks
probabilistic graphical models
machine learning
decision graphs
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Professor
Pan Li
Georgia Institute of Technology
United States of America
graph machine learning
graph neural networks
machine learning
geometric deep learning
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Professor
Nanwei Wang
University of New Brunswick
Canada
bayesian model selection
machine learning
statistical learning
graphical models
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Professor
Hina Shaheen
University of Manitoba
Canada
bayesian inference
machine learning
statistical machine learning
computational modelling
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Professor
Jose Pena
Linköping University
Sweden
bayesian networks
probabilistic graphical models
machine learning
chain graphs
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Professor
Vida Dujmovic
University of Ottawa
Canada
geometric graph theory
structural graph theory
graph theory
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Professor
Danai Koutra
University of Michigan
United States of America
graph machine learning
graph neural networks
graph mining
network representation learning
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Professor
Johan Kwisthout
Radboud University
Netherlands
bayesian networks
probabilistic graphical models
approximate bayesian inference
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Professor
Davide Arioldi
Università della Svizzera italiana
Switzerland
bayesian neural networks
probabilistic graphical models
causal structure learning
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Professor
Xenia Miscouridou
Imperial College London
United Kingdom
bayesian statistical machine learning
bayesian nonparametrics
statistical network modeling
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Professor
Navish Kumar
University of Basel
Switzerland
bayesian inference
spectral graph theory
machine learning
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Professor
Elvin Isufi
Delft University of Technology
Netherlands
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graph machine learning
graph neural networks
graph signal processing
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Professor
Geoff Webb
Monash University
Australia
bayesian machine learning
machine learning
graphical models
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Professor
Prasenjit Ghosh
Texas A&M University
United States of America
bayesian modeling
machine learning
statistical learning
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Professor
Andre Amaral
University of Southampton
United Kingdom
bayesian modelling
machine learning
spatio-temporal statistical modelling
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Professor
Yu Wang
University of New South Wales
Australia
bayesian inference
graph neural networks
geometric deep learning
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Professor
Robin Ryder
Imperial College London
United Kingdom
bayesian computational statistics
approximate bayesian computation
stochastic modelling
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