Sparse Random Graphs Professors in Global

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Ivan Kryven
Utrecht University Netherlands
spectral properties of sparse graphs
random graph representation
random matrices
randomized algorithms
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Elvin Isufi
Delft University of Technology Netherlands
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graph neural networks
graph machine learning
graph signal processing
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Danai Koutra
University of Michigan United States of America
graph mining
graph neural networks
graph machine learning
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Guillaume Conchon--kerjan
King's College London United Kingdom
graphs
random environment
random trees
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Christina Goldschmidt
University of Oxford United Kingdom
graphs
random discrete structures
random trees
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Matthias Winkel
University of Oxford United Kingdom
random hierarchies
random partitions
random trees
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Antti Knowles
University of Geneva Switzerland
random graphs
random matrices
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Giang Tran
University of Waterloo Canada
sparse modeling
sparse optimization methods
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Ian Wassell
University of Cambridge United Kingdom
sparse representation data
sparse image video coding
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Trac-duy Tran
Johns Hopkins University United States of America
sparse representation
sparse recovery
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Leo Benatar
Georgia Institute of Technology United States of America
random graphs
randomized algorithms
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Karen Gunderson
University of Manitoba Canada
random graphs
hypergraphs
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Oanh Nguyen
Brown University United States of America
random graphs
random polynomials
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Nick Wormald
Monash University Australia
random graphs
combinatorial graph algorithms
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Stephan Wagner
Uppsala University Sweden
random graphs
random trees
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Nicholas Cook
Duke University Singapore
random hypergraphs
exponential random graph models
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Pierre Vandergheynst
École Polytechnique Fédérale de Lausanne Switzerland
sparse approximations
graph-based data processing
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Pu Yu
New York University United States of America
random planar maps
random geometry
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Frederi Viens
Michigan State University United States of America
random matrices
random fields
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Theo Assiotis
University of Edinburgh United Kingdom
random matrices
branching graphs
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A.c.c. Coolen
Radboud University Netherlands
random networks
graphs
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