Aleatoric and Epistemic Uncertainty with Random Forests. - Mohammad Hossein Shaker; Eyke Hüllermeier (IDA, 2020)

Drift Detection in Text Data with Document Embeddings. - Robert Feldhans; Adrian Wilke; Stefan Heindorf; Mohammad Hossein Shaker; Barbara Hammer; Axel-Cyrille Ngonga Ngomo; Eyke Hüllermeier (IDEAL, 2021)

Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference. - Mohammad Hossein Shaker; Eyke Hüllermeier (CoRR, 2021)

Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. - Eyke Hüllermeier; Sébastien Destercke; Mohammad Hossein Shaker (UAI, 2022)

How to measure uncertainty in uncertainty sampling for active learning. - Vu-Linh Nguyen; Mohammad Hossein Shaker; Eyke Hüllermeier (Mach. Learn., 2022)

Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data. - Nastaran Saberi; Mohammad Hossein Shaker; Claude R. Duguay; Katharine Andrea Scott; Eyke Hüllermeier (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Random Forest Calibration. - Mohammad Hossein Shaker; Eyke Hüllermeier (CoRR, 2025)