Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. - Christian Tomani; Sebastian Gruber 001; Muhammed Ebrar Erdem; Daniel Cremers; Florian Buettner 001 (CVPR, 2021)

Better Uncertainty Calibration via Proper Scores for Classification and Beyond. - Sebastian G. Gruber; Florian Buettner 001 (NeurIPS, 2022)

Trustworthy Deep Learning via Proper Calibration Errors: A Unifying Approach for Quantifying the Reliability of Predictive Uncertainty. - Sebastian G. Gruber; Florian Buettner 001 (CoRR, 2022)

Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. - Sebastian Gruber 001; Florian Buettner 001 (AISTATS, 2023)

Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. - Teodora Popordanoska; Sebastian Gregor Gruber; Aleksei Tiulpin; Florian Büttner 001; Matthew B. Blaschko (AISTATS, 2024)

A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models. - Sebastian Gregor Gruber; Florian Buettner 001 (ICML, 2024)

Disentangling Mean Embeddings for Better Diagnostics of Image Generators. - Sebastian G. Gruber; Pascal Tobias Ziegler; Florian Buettner 001 (CoRR, 2024)

Application-driven validation of posteriors in inverse problems. - Tim J. Adler; Jan-Hinrich Nölke; Annika Reinke; Minu Dietlinde Tizabi; Sebastian Gruber 001; Dasha Trofimova; Lynton Ardizzone; Paul F. Jaeger; Florian Buettner 001; Ullrich Köthe; Lena Maier-Hein (Medical Image Anal., 2025)

Optimizing Estimators of Squared Calibration Errors in Classification. - Sebastian Gregor Gruber; Francis R. Bach (Trans. Mach. Learn. Res., 2025)

Beyond Segmentation: Confidence-Aware and Debiased Estimation of Ratio-based Biomarkers. - Jiameng Li; Teodora Popordanoska; Sebastian G. Gruber; Frederik Maes; Matthew B. Blaschko (CoRR, 2025)

Revisiting Reweighted Risk for Calibration: AURC, Focal Loss, and Inverse Focal Loss. - Han Zhou 013; Sebastian G. Gruber; Teodora Popordanoska; Matthew B. Blaschko (CoRR, 2025)