November 4 - 8, 2024
Eurandom workshop on graph Laplacians, multivariate extremes and algebraic statistics
Eindhoven, The Netherlands
3-day Workshop
and 2-day Mini-courses
News:
Registration is now open and will close as soon as the maximum capacity is reached, but no later than July 31. Due to limited capacity, participants will be selected based on their profile and interest in the workshop. We will try to confirm your registration as soon as possible.
There is the possibility of presenting a poster, which can be indicated during the registration process.
Dates:
Mini-courses: November 4 - 5, 2024.
Workshop: November 6 - 8, 2024.
Location: Metaforum, Eindhoven University of Technology, Eindhoven, The Netherlands.
Mini-courses:
Mini-course on Graph Signal Processing, taught by Michal Valko (DeepMind Paris).
Mini-course on Graphical Models in Extremes, taught by Sebastian Engelke (University of Geneva).
Mini-course on Graphical Models and Algebraic Statistics, taught by Jane Ivy Coons (University of Oxford).
Confirmed Participants:
Aida Abiad Monge (Eindhoven University of Technology)
Carlos Améndola (TU Berlin)
Jane Ivy Coons (University of Oxford)
Karel Devriendt (MPI MiS Leipzig)
Ignacio Echave-Sustaeta Rodríguez (Eindhoven University of Technology)
Sebastian Engelke (University of Geneva)
Nicola Gnecco (UCL)
Steffen Lauritzen (University of Copenhagen)
Pratik Misra (TU Munich)
Alberto Natali (TU Delft)
Marco Oesting (University of Stuttgart)
Frank Röttger (Eindhoven University of Technology)
Johan Segers (UC Louvain)
Kirstin Strokorb (Cardiff University)
Michal Valko (DeepMind Paris)
Mariana Vargas Vieyra (MOSTLY AI)
Phyllis Wan (Erasmus University Rotterdam)
Chen Zhou (Erasmus University Rotterdam)
Piotr Zwiernik (University of Toronto)
Outline:
The idea for this workshop is to bring together researchers from graph signal processing, multivariate extremes and graphical models/ algebraic statistics to discuss theoretical and methodological intersections and to foster future collaborations. Some key points of interest:
Laplacian matrices in graphical extremes and graph signal processing.
Sparsity in graph Laplacians: Extremal conditional independence, CI ideals and sparse signals.
Algebraic statistics and graphical extremes.
Graph Laplacians and Euclidean distance matrices: Combinatorial and geometric tools for statistics.
Statistical Graph Signal Processing.
Learning in graph data, representation learning in graphs.
Inference of graph topology.
Geometric Deep Learning.
Applications of Graph Signal Processing on network-structured data (such as in communication networks, health care, social networks, drug discovery).
Phishing warning:
Scientific workshops are unfortunately frequent phishing targets. Please contact one of the organizers when in doubt.
Organizers:
Ignacio Echave-Sustaeta Rodríguez (Eindhoven University of Technology)
Frank Röttger (Eindhoven University of Technology)
Mariana Vargas Vieyra (MOSTLY AI)
Piotr Zwiernik (University of Toronto)