CrashNet: an encoder-decoder architecture to predict crash test outcomes. - Mohamed Karim Belaid; Maximilian Rabus; Ralf Krestel (Data Min. Knowl. Discov., 2021)

Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark. - Mohamed Karim Belaid; Eyke Hüllermeier; Maximilian Rabus; Ralf Krestel (CoRR, 2022)

Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark. - Mohamed Karim Belaid; Richard Bornemann; Maximilian Rabus; Ralf Krestel; Eyke Hüllermeier (xAI (2), 2023)

Optimizing Data Shapley Interaction Calculation from O(2^n) to O(t n^2) for KNN models. - Mohamed Karim Belaid; Dorra El Mekki; Maximilian Rabus; Eyke Hüllermeier (CoRR, 2023)

Pairwise Difference Learning for Classification. - Mohamed Karim Belaid; Maximilian Rabus; Eyke Hüllermeier (DS (2), 2024)

LossVal: Efficient Data Valuation for Neural Networks. - Tim Wibiral; Mohamed Karim Belaid; Maximilian Rabus; Ansgar Scherp (CoRR, 2024)