2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Learning the Markov order of paths in a network
Luka V. Petrović, Ingo Scholtes
We study the problem of learning the Markov order in categorical sequences that represent paths in a network, i.e. sequences of variable lengths where transitions between states ar…
cs.SI2019
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…
cs.SI2019
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…