3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Model-agnostic Mitigation Strategies of Data Imbalance for Regression
Jelke Wibbeke, Sebastian Rohjans, Andreas Rauh
Data imbalance persists as a pervasive challenge in regression tasks, introducing bias in model performance and undermining predictive reliability. This is particularly detrimental…
cs.LG2026★ 3 cited
Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models
Jelke Wibbeke, Nico Schönfisch, Sebastian Rohjans +1
In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonly referred to as calibration, is…