3 papers
astro-ph.HE2026
Learning Neural Operator Surrogates for the Black Hole Accretion Code
Matthias Nägele, Cedric Bös, Chester Tan +3
General-relativistic magnetohydrodynamic (GR-MHD) simulations are essential for studying black hole accretion, relativistic jets, and magnetic reconnection, yet their computational…
cs.LG2025
Link Prediction with Untrained Message Passing Layers
Lisi Qarkaxhija, Anatol E. Wegner, Ingo Scholtes
Message passing neural networks (MPNNs) operate on graphs by exchanging information between neigbouring nodes. MPNNs have been successfully applied to various node-, edge-, and gra…
cs.LG2024
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
Christopher Blöcker, Chester Tan, Ingo Scholtes
Community detection is an essential tool for unsupervised data exploration and revealing the organisational structure of networked systems. With a long history in network science,…