Paper on Explainable Machine Learning published

Scarlet Stadtler, Clara Betancourt (FZ Jülich) and Ribana Roscher (University of Bonn) published their study on “Explainable Machine Learning Reveals Capabilities, Redundancy, and Limitations of a Geospatial Air Quality Benchmark Dataset” in the Machine Learning and Knowledge Extraction Journal. In their study, they gained insights into the AQ-Bench dataset on air quality using explainable machine learning. The article is available at