RUN-CSP: Unsupervised Learning of Message Passing Networks for Binary Constraint Satisfaction Problems. - Jan Tönshoff; Martin Ritzert; Hinrikus Wolf; Martin Grohe (CoRR, 2019)

The Effects of Randomness on the Stability of Node Embeddings. - Tobias Schumacher 002; Hinrikus Wolf; Martin Ritzert; Florian Lemmerich; Jan Bachmann; Florian Frantzen; Max Klabunde; Martin Grohe; Markus Strohmaier (CoRR, 2020)

Graph Neural Networks for Maximum Constraint Satisfaction. - Jan Tönshoff; Martin Ritzert; Hinrikus Wolf; Martin Grohe (Frontiers Artif. Intell., 2020)

The Effects of Randomness on the Stability of Node Embeddings. - Tobias Schumacher 002; Hinrikus Wolf; Martin Ritzert; Florian Lemmerich; Martin Grohe; Markus Strohmaier (PKDD/ECML Workshops (1), 2021)

Graph Learning with 1D Convolutions on Random Walks. - Jan Tönshoff; Martin Ritzert; Hinrikus Wolf; Martin Grohe (CoRR, 2021)

Solving AC Power Flow with Graph Neural Networks under Realistic Constraints. - Luis Böttcher; Hinrikus Wolf; Bastian Jung; Philipp Lutat; Marc Trageser; Oliver Pohl; Andreas Ulbig; Martin Grohe (CoRR, 2022)

Structural Node Embeddings with Homomorphism Counts. - Hinrikus Wolf; Luca Oeljeklaus; Pascal Kühner; Martin Grohe (CoRR, 2023)

Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing. - Jan Tönshoff; Martin Ritzert; Hinrikus Wolf; Martin Grohe (Trans. Mach. Learn. Res., 2023)

End-to-End Reinforcement Learning of Curative Curtailment with Partial Measurement Availability. - Hinrikus Wolf; Luis Böttcher; Sarra Bouchkati; Philipp Lutat; Jens Breitung; Bastian Jung; Tina Möllemann; Viktor Todosijevic; Jan Schiefelbein-Lach; Oliver Pohl; Andreas Ulbig; Martin Grohe (ISGT EUROPE, 2024)

Learning on graphs from theory to industrial application in power management of distribution grids. - Hinrikus Wolf (2024)