4 citations · 4 across the 2 of their papers we have counts for
4 papers
Causal inference in partially linear structural equation models
Dominik Rothenhäusler, Jan Ernest, Peter Bühlmann
We consider identifiability of partially linear additive structural equation models with Gaussian noise (PLSEMs) and estimation of distributionally equivalent models to a given PLS…
Nonparametric causal inference from observational time series through marginal integration
Shu Li, Jan Ernest, Peter Bühlmann
Causal inference from observational data is an ambitious but highly relevant task, with diverse applications ranging from natural to social sciences. Within the scope of nonparamet…
Marginal integration for nonparametric causal inference
Jan Ernest, Peter Bühlmann
We consider the problem of inferring the total causal effect of a single variable intervention on a (response) variable of interest. We propose a certain marginal integration regre…
CAM: Causal additive models, high-dimensional order search and penalized regression
Peter Bühlmann, Jonas Peters, Jan Ernest
We develop estimation for potentially high-dimensional additive structural equation models. A key component of our approach is to decouple order search among the variables from fea…