Universität Bonn

Institute of Computer Science

15. May 2024

Colloquium: Research Talk by Prof. Dr. Ingo Scholtes Colloquium: Research Talk by Prof. Dr. Ingo Scholtes on May 23

Colloquium: Research Talk by Prof. Dr. Ingo Scholtes
Colloquium: Research Talk by Prof. Dr. Ingo Scholtes © Unsplash
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We cordially invite you to the colloquium of Prof. Dr. Ingo Scholtes!

On May 23, 2024, from 12:30 p.m. to 13:30 p.m., Prof. Dr. Ingo Scholtes will give a research talk. He is Professor for Machine Learning in Complex Networks at the Center for Artificial Intelligence and Data Science of the University Würzburg, as well as SNSF Professor for Data Analytics at the University Zurich (Switzerland).

The research talk is dedicated to the topic "The Arrow of Time in Temporal Graphs: From Laplacian Dynamics to De Bruijn Graph Neural Networks".


Graph Neural Networks have become an important paradigm in the application of machine learning to data on complex systems with many interacting elements. Apart from relational data that captures which of a system's elements are connected, we increasingly have access to high-resolution time series data that captures when and in which order those connections occur. Due to the arrow of time, the temporal order of those connections shapes the causal topology of temporal graphs, i.e. which nodes can possibly causally influence each other over time. This leads to non-trivial effects that must be accounted for in the modelling of dynamical processes in graph with dynamic topologies.

Addressing this issue, I will show that the spectral properties of higher-order De Bruijn Graphs can help us to better understand how the arrow of time influences the evolution of dynamical processes in temporal graphs. Apart from improving our understanding of social, technical and biological networks with dynamic topologies, these models are the theoretical foundation for De Bruijn Graph Neural Networks, a new time-aware deep learning architecture for temporal graph data. Accounting for temporal-topological patterns in temporal graphs, our approach facilitates deep graph learning in time series data on complex networks.

The event is free of charge. Interested individuals are warmly invited to attend!

When? Thursday, May 23 2024, 12:30 p.m. to 13:30 p.m.

Where? Institute for Computer Science, Friedrich-Hirzebruch-Allee 5, 53113 Bonn, Room 0.016

Michaela Musselmann
Institute of Computer Science
University of Bonn
Phone.: +49 228 73-4502
Mail: musselmann@iai.uni-bonn.de

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