activity
20222025
most citedOne Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE2025

Bursts and Triggers: Socially-Driven Activity in Open-Source Co-Editing Networks

Lisi Qarkaxhija, Maximilian Capraro, Stefan Menzel +2

The long-term sustainability of Open Source Software (OSS) communities depends on the activity of their developers, yet the social mechanisms driving this collective behavior remai…

cs.LG2024

Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs

Jan von Pichowski, Vincenzo Perri, Lisi Qarkaxhija +1

The modelling of temporal patterns in dynamic graphs is an important current research issue in the development of time-aware GNNs. Whether or not a specific sequence of events in a…

cs.LG2024

Link Prediction with Untrained Message Passing Layers

Lisi Qarkaxhija, Anatol E. Wegner, Ingo Scholtes

Message passing neural networks (MPNNs) operate on graphs by exchanging information between neigbouring nodes. MPNNs have been successfully applied to various node-, edge-, and gra…

cs.CL20222 cited

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…

cs.LG20221 cited

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…