Meinshausen, Nicolai

13 publications

ICLRW 2025 Representation Learning for Distributional Perturbation Extrapolation Julius von Kügelgen, Xinwei Shen, Jakob Ketterer, Nicolai Meinshausen, Jonas Peters

JMLR 2023 Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf, Corinne Emmenegger, Peter Bühlmann, Nicolai Meinshausen

JMLR 2022 Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression Domagoj Cevid, Loris Michel, Jeffrey Näf, Peter Bühlmann, Nicolai Meinshausen

NeurIPS 2022 Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit

MLJ 2021 Conditional Variance Penalties and Domain Shift Robustness Christina Heinze-Deml, Nicolai Meinshausen

JMLR 2020 Fair Data Adaptation with Quantile Preservation Drago Plečko, Nicolai Meinshausen

JMLR 2020 Spectral Deconfounding via Perturbed Sparse Linear Models Domagoj Ćevid, Peter Bühlmann, Nicolai Meinshausen

JMLR 2018 The Xyz Algorithm for Fast Interaction Search in High-Dimensional Data Gian-Andrea Thanei, Nicolai Meinshausen, Rajen D. Shah

AISTATS 2016 DUAL-LOCO: Distributing Statistical Estimation Using Random Projections Christina Heinze, Brian McWilliams, Nicolai Meinshausen

NeurIPS 2016 Scalable Adaptive Stochastic Optimization Using Random Projections Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M Buhmann, Nicolai Meinshausen

NeurIPS 2015 BACKSHIFT: Learning Causal Cyclic Graphs from Unknown Shift Interventions Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen

JMLR 2014 Random Intersection Trees Rajen Dinesh Shah, Nicolai Meinshausen

JMLR 2006 Quantile Regression Forests Nicolai Meinshausen