Higher-Order Visualization of Causal Structures in Dynamics Graphs. - Vincenzo Perri; Ingo Scholtes (CoRR, 2019)

HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs. - Vincenzo Perri; Ingo Scholtes (GD, 2020)

Analysis and Visualisation of Time Series Data on Networks with Pathpy. - Jürgen Hackl; Ingo Scholtes; Luka V. Petrovic; Vincenzo Perri; Luca Verginer; Christoph Gote (WWW (Companion Volume), 2021)

Visualisation of Temporal Network Data via Time-Aware Static Representations with HOTVis. - Vincenzo Perri; Ingo Scholtes (WWW (Companion Volume), 2021)

Predicting Influential Higher-Order Patterns in Temporal Network Data. - Christoph Gote; Vincenzo Perri; Ingo Scholtes (ASONAM, 2022)

One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium. - Vincenzo Perri; Lisi Qarkaxhija; Albin Zehe; Andreas Hotho; Ingo Scholtes (CHR, 2022)

De Bruijn Goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs. - Lisi Qarkaxhija; Vincenzo Perri; Ingo Scholtes (LoG, 2022)

Bayesian Detection of Mesoscale Structures in Pathway Data on Graphs. - Luka V. Petrovic; Vincenzo Perri (CoRR, 2023)

Bayesian inference of transition matrices from incomplete graph data with a topological prior. - Vincenzo Perri; Luka V. Petrovic; Ingo Scholtes (EPJ Data Sci., 2023)

Locating community smells in software development processes using higher-order network centralities. - Christoph Gote; Vincenzo Perri; Christian Zingg; Giona Casiraghi; Carsten Arzig; Alexander von Gernler; Frank Schweitzer; Ingo Scholtes (Soc. Netw. Anal. Min., 2023)

Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs. - Jan von Pichowski; Vincenzo Perri; Lisi Qarkaxhija; Ingo Scholtes (CoRR, 2024)