Score: 0

Lecture Notes on Verifying Graph Neural Networks

Published: October 13, 2025 | arXiv ID: 2510.11617v1

By: François Schwarzentruber

Potential Business Impact:

Checks computer programs for mistakes using logic.

Business Areas:
Semantic Web Internet Services

In these lecture notes, we first recall the connection between graph neural networks, Weisfeiler-Lehman tests and logics such as first-order logic and graded modal logic. We then present a modal logic in which counting modalities appear in linear inequalities in order to solve verification tasks on graph neural networks. We describe an algorithm for the satisfiability problem of that logic. It is inspired from the tableau method of vanilla modal logic, extended with reasoning in quantifier-free fragment Boolean algebra with Presburger arithmetic.

Page Count
65 pages

Category
Computer Science:
Logic in Computer Science