5 citations · 9 across the 7 of their papers we have counts for
6 papers · 1 filter
MeGA-MP: Metric Graph Advection Message Passing -- A Physics-Informed Message Passing Operator for Advection-Dominated Metric Graphs
Janine Strotherm, Luca Hermes, André Artelt +1
Many real-world systems are organized as networks where spatio-temporal dynamics unfold along connections and not discretely between nodes. Examples include utility networks such a…
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto +5
Albeit the ubiquitous use of Graph Neural Networks (GNNs) in machine learning (ML) prediction tasks involving graph-structured data, their interpretability remains challenging. In…
Fairness-Enhancing Ensemble Classification in Water Distribution Networks
Janine Strotherm, Barbara Hammer
As relevant examples such as the future criminal detection software [1] show, fairness of AI-based and social domain affecting decision support tools constitutes an important area…
Challenges, Methods, Data -- a Survey of Machine Learning in Water Distribution Networks
Valerie Vaquet, Fabian Hinder, André Artelt +5
Research on methods for planning and controlling water distribution networks gains increasing relevance as the availability of drinking water will decrease as a consequence of clim…
Physics-Informed Graph Neural Networks for Water Distribution Systems
Inaam Ashraf, Janine Strotherm, Luca Hermes +1
Water distribution systems (WDS) are an integral part of critical infrastructure which is pivotal to urban development. As 70% of the world's population will likely live in urban e…
Fairness in KI-Systemen
Janine Strotherm, Alissa Müller, Barbara Hammer +1
The more AI-assisted decisions affect people's lives, the more important the fairness of such decisions becomes. In this chapter, we provide an introduction to research on fairness…