In our new paper Modeling Social Resilience: Questions, Answers, Open Problems, which was recently published in Advances in Complex Systems, we present a modelling framework that captures two dimensions of resilience: robustness and adaptivity.
moreWe are happy to learn that Prof. Dr. Ingo Scholtes has received a Best Reviewer Award at the Learning on Graphs Conference.
moreWe have just released a new preprint on De Bruijn Graph Neural Networks, a new approach to time-aware graph learning that leverages the causal topology of time-stamped network data.
moreOur manuscript Predicting Influential Higher-Order Patterns in Temporal Network Data has been accepted for publication at the IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM 2022).
moreOur manuscript Sequential Motifs in Observed Walks has just been published online in the interdisciplinary Journal of Complex Networks.
moreToday, Prof. Ingo Scholtes will give a lecture on higher-order graph models at the Summer School on Mathematics of Complex Social Systems, which is held at the Berlin Mathematics Research Center Math+, Germany.
moreWe are happy to learn that our poster submission Willing to revise? Confidence and Recommendation Adoption in AI-Assisted Image Recognition has been accepted at the International Conference on Hybrid Human-Artificial Intelligence in Amsterdam, Netherlands.
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On January 14th, Prof. Dr. Ingo Scholtes will give a talk in the AI Talks @ JMU series. The talk with the title "What makes teams successful? Insights from Repository Mining, Network Science, and Empirical Software Engineering" addresses the question how we can use massive data on software repositories to gain insights into collaborative software engineering.
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The final report of our Dagstuhl Seminar on "Higher-Order Graph Models: From Theoretical Foundations to Machine Learning" has now been published in the series Dagstuhl Reports of the Leibniz Zentrum für Informatik.
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Today, we welcome our new team member Chester Tan, who is joining our chair as a PhD student.
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We are delighted to welcome Dr. Anatol Wegner, who has joined our chair as a postdoctoral researcher.
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In our recent preprint "Sequential Motifs in Observed Walks" we use higher-order graph models for causal paths to analyze patterns in time series data on networks. The study has been led by collaborators at Northeastern University in Boston, USA.
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We wish all of you merry Christmas, happy holidays, and a good start into a successful and - most importantly - healthy new year!
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Given the observation of a dynamical process in an an unobserved networked system, what can we say about the underlying interaction topology? Our latest study led by Dr. Unai Alvarez-Rodriguez addresses this important question.
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We are happy to announce that our latest study "Big Data = Big Insights? Operationalizing Brooks’ Law in a Massive GitHub Data Set" was accepted for the technical track of the 44th International Conference on Software Engineering (ICSE), to be held in May 2022 in Philadelphia, PA, USA.
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