24 citations · 109 across the 28 of their papers we have counts for
5 papers · 1 filter
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…
A Toolbox for Supporting Research on AI in Water Distribution Networks
André Artelt, Marios S. Kyriakou, Stelios G. Vrachimis +3
Drinking water is a vital resource for humanity, and thus, Water Distribution Networks (WDNs) are considered critical infrastructures in modern societies. The operation of WDNs is…
Towards Understanding the Influence of Training Samples on Explanations
André Artelt, Barbara Hammer
Explainable AI (XAI) is widely used to analyze AI systems' decision-making, such as providing counterfactual explanations for recourse. When unexpected explanations occur, users ma…
A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations
André Artelt, Andreas Gregoriades
Counterfactual explanations constitute among the most popular methods for analyzing black-box systems since they can recommend cost-efficient and actionable changes to the input of…
The Effect of Data Poisoning on Counterfactual Explanations
André Artelt, Shubham Sharma, Freddy Lecué +1
Counterfactual explanations are a widely used approach for examining the predictions of black-box systems. They can offer the opportunity for computational recourse by suggesting a…