Bayesian Graph Structure Learning Professors in Global

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