314 citations · 444 across the 20 of their papers we have counts for
7 papers · 1 filter
Modeling social resilience: Questions, answers, open problems
Frank Schweitzer, Georges Andres, Giona Casiraghi +5
Resilience denotes the capacity of a system to withstand shocks and its ability to recover from them. We develop a framework to quantify the resilience of highly volatile, non-equi…
Bayesian Inference of Transition Matrices from Incomplete Graph Data with a Topological Prior
Vincenzo Perri, Luka V. Petrović, Ingo Scholtes
Many network analysis and graph learning techniques are based on models of random walks which require to infer transition matrices that formalize the underlying stochastic process…
One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium
Vincenzo Perri, Lisi Qarkaxhija, Albin Zehe +2
Natural Language Processing and Machine Learning have considerably advanced Computational Literary Studies. Similarly, the construction of co-occurrence networks of literary charac…
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs
Lisi Qarkaxhija, Vincenzo Perri, Ingo Scholtes
We introduce De Bruijn Graph Neural Networks (DBGNNs), a novel time-aware graph neural network architecture for time-resolved data on dynamic graphs. Our approach accounts for temp…
Similarity-based Link Prediction from Modular Compression of Network Flows
Christopher Blöcker, Jelena Smiljanić, Ingo Scholtes +1
Node similarity scores are a foundation for machine learning in graphs for clustering, node classification, anomaly detection, and link prediction with applications in biological s…
Big Data = Big Insights? Operationalising Brooks' Law in a Massive GitHub Data Set
Christoph Gote, Pavlin Mavrodiev, Frank Schweitzer +1
Massive data from software repositories and collaboration tools are widely used to study social aspects in software development. One question that several recent works have address…