no code implementations • 5 Jun 2023 • Kirk Bansak, Elisabeth Paulson, Dominik Rothenhäusler
Thus, we consider a class of random distribution shift models that capture arbitrary changes in the underlying covariate space, and dense, random shocks to the relationship between the covariates and the outcomes.
1 code implementation • 7 May 2021 • Suyash Gupta, Dominik Rothenhäusler
We evaluate the performance of the proposed measure on real data and show that it can elucidate the distributional instability of a parameter with respect to certain shifts and can be used to improve estimation accuracy under shifted distributions.
2 code implementations • 18 Jan 2018 • Dominik Rothenhäusler, Nicolai Meinshausen, Peter Bühlmann, Jonas Peters
If anchor regression and least squares provide the same answer (anchor stability), we establish that OLS parameters are invariant under certain distributional changes.
Methodology
1 code implementation • NeurIPS 2015 • Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen
We propose a simple method to learn linear causal cyclic models in the presence of latent variables.