UnRAVeL-Ringvorlesung: Martin Grohe: The Logic of Graph Neural Networks
Donnerstag, 20.05.2021, 16.30 Uhr
Vortragender: Martin Grohe
Graph neural networks (GNNs) are a deep learning architecture for graph structured data that has developed into a method of choice for many graph learning problems in recent years. It is therefore important that we understand their power. One aspect of this is the expressiveness: which functions on graphs can be expressed by a GNN model? Surprisingly, this question has a precise answer in terms of logic and a combinatorial algorithm known as the Weisfeiler Leman algorithm.
In my lecture, I will introduce the basic GNN architecture and also some extensions, and I will explain the logical characterisations of their expressiveness.
The talks of the UnRAVeL survey lecture 2021 will be given via Zoom every Thursday from 16:30 to 18:00:
Meeting ID: 960 4371 5437