# Survey Lecture: Martin Grohe: The Logic of Graph Neural Networks

### Thursday, May 20, 2021, 4:30pm

Speaker: Martin Grohe

Abstract:

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

Passcode: 039217