6 citations · 16 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach
Niklas Pfister, Stefan Bauer, Jonas Peters
Learning kinetic systems from data is one of the core challenges in many fields. Identifying stable models is essential for the generalization capabilities of data-driven inference…
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables
Rune Christiansen, Jonas Peters
Given a response and a vector of predictors, we investigate the problem of inferring direct causes of among the vector . Models for that…
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure
Rajen D. Shah, Jonas Peters
It is a common saying that testing for conditional independence, i.e., testing whether whether two random vectors and are independent, given , is a hard statistical prob…
Anchor regression: heterogeneous data meets causality
Dominik Rothenhäusler, Nicolai Meinshausen, Peter Bühlmann +1
We consider the problem of predicting a response variable from a set of covariates on a data set that differs in distribution from the training data. Causal parameters are optimal…