Statistical comparisons of spatio-temporal networks | Vidéo | Carmin.tv

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Statistical comparisons of spatio-temporal networks

By Sophie Achard

Appears in collection : Machine Learning and Signal Processing on Graphs / Apprentissage automatique et traitement du signal sur graphes

In the scenario where multiple instances of networks with same nodes are available and nodes are attached to spatial features, it is worth combining both information in order to explain the role of the nodes. The explainability of node role in complex networks is very difficult, however crucial in different application scenarios such as social science, neuroscience, computer science... Many efforts have been made on the quantification of hubs revealing particular nodes in a network using a given structural property. Yet, for spatio-temporal networks, the identification of node role remains largely unexplored. In this talk, I will show limitations of classical methods on a real datasets coming from brain connectivity comparing healthy subjects to coma patients. Then, I will present recent work using equivalence relation of the nodal structural properties. Comparisons of graphs with same nodes set is evaluated with a new similarity score based on graph structural patterns. This score provides a nodal index to determine node role distinctiveness in a graph family. Finally, illustrations on different datasets concerning human brain functional connectivity will be described.

Information about the video

Date of recording 07/11/2022
Date of publication 05/12/2022
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers, Graduate Students
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.19981403
Cite this video Achard, Sophie (07/11/2022). Statistical comparisons of spatio-temporal networks. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19981403
URL https://dx.doi.org/10.24350/CIRM.V.19981403

Domain(s)

Quantitative Biology

Bibliography

CARBONI, Lucrezia, DOJAT, Michel, et ACHARD, Sophie. Nodal statistics-based equivalence relation for graph collections. arXiv preprint arXiv:2210.01053, 2022. - https://doi.org/10.48550/arXiv.2210.01053

MSC codes

Document(s)

https://www.cirm-math.fr/RepOrga/2588/Slides/achard.pdf

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