Publications
We follow an interdisciplinary publication strategy that targets key venues in data science, machine learning, and software engineering as well as journals in fields like information science, statistics, complex systems, or theoretical physics.
Our works have been published in conferences like SIGKDD, ICSE, MSR, Graph Drawing, and SIAM Data Mining, as well as in journals like Physical Review Letters, Nature Physics, Nature Communications, Scientometrics, Empirical Software Engineering, and EPJ Data Science.
Below, we only list the most recent publications. Please refer to the profile page of Prof. Scholtes to get an comprehensive overview of all past publications of the chair holder.
- Christoph Gote, Ingo Scholtes, Pavlin Mavrodiev, Frank Schweitzer
Big Data = Big Insights? Operationalizing Brooks’ Law in a Massive GitHub Data Set
To appear in Proceedings of the 44th International Conference on Software Engineering (ICSE 2022), Pittsburgh, PA, USA, May 2022
- Timothy LaRock, Ingo Scholtes, Tina Eliassi-Rad
Sequential Motifs in Observed Walks
preprint, December 2021, arXiv 2112.05642
- Tina Eliassi-Rad, Vito Latora, Martin Rosvall, Ingo Scholtes
Higher-Order Graph Models: From Theoretical Foundations to Machine Learning (Dagstuhl Seminar 21352)
Dagstuhl Reports, Vol. 11, No. 7, pp. 139 -- 178, December 2021
- Unai Alvarez-Rodriguez, Luka Petrovic, Ingo Scholtes
Inference of time-ordered multibody interactions
preprint, November 2021, arXiv 2111.14611
- Christoph Gote, Ingo Scholtes and Frank Schweitzer
Analysing Time-Stamped Co-Editing Networks in Software Development Teams using git2net
In Empirical Software Engineering, May 26, 2021
[arXiv 1911.09484] [SpringerLink]
- Jürgen Hackl, Ingo Scholtes, Luka V Petrović, Vincenzo Perri, Luca Verginer, Christoph Gote
Analysis and visualisation of time series data on networks with pathpy
In Proceedings of the 11th Temporal Web Analytics Workshop (TempWeb 2021) in conjunction with The Web Conference 2021, Ljubljana, Slovenia, April 2021
- Vincenzo Perri and Ingo Scholtes
Visualisation of Temporal Network Data via Time-Aware Static Representations with HOTVis
In Proceedings of the 11th Temporal Web Analytics Workshop (TempWeb 2021) in conjunction with The Web Conference 2021, Ljubljana, Slovenia, April 2021
- Luka Petrović and Ingo Scholtes
PaCo: Fast Counting of Causal Paths in Temporal Network Data
In Proceedings of the 11th Temporal Web Analytics Workshop (TempWeb 2021) in conjunction with The Web Conference 2021, Ljubljana, Slovenia, April 2021
[arXiv 1905.11287]
- Yan Zhang, Antonios Garas and Ingo Scholtes
Higher-order models capture changes in controllability of temporal networks
In Journal of Physics: Complexity, Vol. 2, No. 1, January 29, 2021
[DOI] [arXiv 1701.06331]
- Vincenzo Perri and Ingo Scholtes
HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs
In Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD 2020), Vancouver, BC, Canada, September 15-18, 2020
[DOI] [arXiv 1908.05976] [DBLP BibTeX]
- Timothy LaRock, Vahan Nanumyan, Ingo Scholtes, Giona Casiraghi, Tina Eliassi-Rad and Frank Schweitzer
HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
In Proceedings of SIAM International Conference on Data Mining (SDM 2020), May 7-9 2020
[DOI] [DBLP BibTeX] [arXiv 1905.10580]
- Christoph Gote, Giona Casiraghi, Frank Schweitzer, Ingo Scholtes
Predicting Sequences of Traversed Nodes in Graphs using Network Models with Multiple Higher Orders
under review, July 2020
[arXiv 2007.06662]
- Luka Petrović and Ingo Scholtes
Learning the Markov order of paths in a network
under review, July 2020
[arXiv 2007.02861]
- Christoph Gote, Ingo Scholtes
git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories
In Proceedings of the 16th International Conference on Mining Software Repositories, MSR 2019, Montreal, QC, Canada, May 2019
[MSR 2019 Website] [arXiv 1903.10180] [DBLP BibTeX] [Reproducibility repository]
- Renaud Lambiotte, Martin Rosvall, Ingo Scholtes
From Networks to Optimal Higher-Order Models of Complex Systems
In Nature Physics, Vol. 15, p. 313-320, March 25 2019