6 citations · 10 across the 8 of their papers we have counts for
3 papers · 1 filter
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…