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Taught graph machine learning at the Geilo Winter School

Associate professor Benjamin Ricaud was one of three invited lecturers at the 24th Geilo Winter School. His presentations focused on graph spectral theory, graph signal processing and their connection to graph machine learning.

Taught graph machine learning at the Geilo Winter School

By: Petter Bjørklund, Communications Advisor, Visual Intelligence

The 24th Geilo Winter School took place in Geilo, Norway from January 21st-26th 2024. The program covered topics related to graphs and applications.

Associate professor Benjamin Ricaud (UiT Machine Learning Group/Visual Intelligence) was one of three invited lecturers at the school. His presentations focused on graph spectral theory, graph signal processing and their connection to graph machine learning.

Benjamin Ricaud. Photo: private

- I also explained the central role of the Graph Laplacian when working with graphs and why it appears in graph neural networks, says Ricaud. He adds that he finished with an opening to some new directions in graph and machine learning, particularly with dynamic data on graphs.

Ricaud is thankful that he was invited as a lecturer at the winter school, stating that he is always happy to talk about graphs and data analysis on graphs.

- The school was well organized with a long break in the middle of the program to enjoy the sun and go skiing, concludes Ricaud.

The Geilo Winter School was organized by SINTEF.

Ricaud (fourth row and first to the left) alongside other participants at Geilo Winter School. Photo: Torkel Haufmann

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