314 citations · 444 across the 20 of their papers we have counts for
6 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…
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…
Predicting Influential Higher-Order Patterns in Temporal Network Data
Christoph Gote, Vincenzo Perri, Ingo Scholtes
Networks are frequently used to model complex systems comprised of interacting elements. While edges capture the topology of direct interactions, the true complexity of many system…
HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs
Vincenzo Perri, Ingo Scholtes
Network visualisation techniques are important tools for the exploratory analysis of complex systems. While these methods are regularly applied to visualise data on complex network…
Counting Causal Paths in Big Times Series Data on Networks
Luka V. Petrovic, Ingo Scholtes
Graph or network representations are an important foundation for data mining and machine learning tasks in relational data. Many tools of network analysis, like centrality measures…
HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
Timothy LaRock, Vahan Nanumyan, Ingo Scholtes +3
The unsupervised detection of anomalies in time series data has important applications in user behavioral modeling, fraud detection, and cybersecurity. Anomaly detection has, in fa…