Dominik Rothenhäusler

8 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0001-5175-9074

Department of Statistics, Stanford University

Publications

• Calibrated Inference: Statistical Inference that Accounts for Both Sampling Uncertainty and Distributional Uncertainty — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Tailored inference for finite populations: conditional validity and transfer across distributions — Biometrika 2024
• On the statistical role of inexact matching in observational studies — Biometrika 2023
• Modular Regression: Improving Linear Models by Incorporating Auxiliary Data — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Causal Aggregation: Estimation and Inference of Causal Effects by Constraint-Based Data Fusion — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Anchor regression: Heterogeneous data meet causality — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2021
• Causal Dantzig: Fast inference in linear structural equation models with hidden variables under additive interventions — The Annals of Statistics 2019
• Out-of-distribution generalization under random, dense distributional shifts — Journal of the American Statistical Association