314 citations · 444 across the 20 of their papers we have counts for
23 papers
Do Temporal Link Predictors Need Learned Memory? A Smoothed-Count Baseline with a Handful of Parameters
Lisi Qarkaxhija, Ingo Scholtes
Many temporal link predictors summarize past interactions through learned node representations. We examine whether simple counts of recurring interaction patterns can provide compe…
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…
Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs
Jan von Pichowski, Vincenzo Perri, Lisi Qarkaxhija +1
The modelling of temporal patterns in dynamic graphs is an important current research issue in the development of time-aware GNNs. Whether or not a specific sequence of events in a…
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…
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,…
A Network Perspective on the Influence of Code Review Bots on the Structure of Developer Collaborations
Leonore Röseler, Ingo Scholtes, Christoph Gote
Background: Despite a growing body of literature on the impact of software bots on open source software development teams, their effects on team communication, coordination, and co…