3 papers
cs.SI2024
Compressing regularized dynamics improves link prediction with the map equation in sparse networks
Maja Lindström, Christopher Blöcker, Tommy Löfstedt +1
Predicting future interactions or novel links in networks is an indispensable tool across diverse domains, including genetic research, online social networks, and recommendation sy…
cs.LG2024
From Link Prediction to Forecasting: Addressing Challenges in Batch-based Temporal Graph Learning
Moritz Lampert, Christopher Blöcker, Ingo Scholtes
Dynamic link prediction is an important problem considered in many recent works that propose approaches for learning temporal edge patterns. To assess their efficacy, models are ev…
cs.SI2020
Mapping Flows on Bipartite Networks
Christopher Blöcker, Martin Rosvall
Mapping network flows provides insight into the organization of networks, but even though many real-networks are bipartite, no method for mapping flows takes advantage of the bipar…