2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2026
Hierarchies of Calibration: Classification meets Regression
Johannes Resin, Lu Yang, Tilmann Gneiting
Concepts of calibration formalize the compatibility between probabilistic predictions and the respective outcomes. In a nutshell, the outcomes ought to be indistinguishable from ra…
stat.ME2024
Shift-Dispersion Decompositions of Wasserstein and Cramér Distances
Johannes Resin, Daniel Wolffram, Johannes Bracher +1
Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositio…
stat.ME2023★ 2 cited
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions
Johannes Resin
In the face of uncertainty, the need for probabilistic assessments has long been recognized in the literature on forecasting. In classification, however, comparative evaluation of…