3 papers
cs.LG2026
RAwR: Role-Aware Rewiring via Approximate Equitable Partition
Riccardo Porcedda, Giuseppe Squillace, Bastian Epping +4
While Graph Neural Networks (GNNs) have demonstrated significant efficacy in node classification tasks, where predictions rely on local neighborhood information, the performance of…
cond-mat.dis-nn2025
Beyond-mean-field fluctuations for the solution of constraint satisfaction problems
Niklas Foos, Bastian Epping, Jannik Grundler +5
Constraint Satisfaction Problems (CSPs) lie at the heart of complexity theory and find application in a plethora of prominent tasks ranging from cryptography to genetics. Classical…
stat.ML2024
Graph Neural Networks Do Not Always Oversmooth
Bastian Epping, Alexandre René, Moritz Helias +1
Graph neural networks (GNNs) have emerged as powerful tools for processing relational data in applications. However, GNNs suffer from the problem of oversmoothing, the property tha…