351 citations · 1.8k across the 37 of their papers we have counts for
3 papers · 2 filters
Causal Inference on Time Series using Structural Equation Models
Jonas Peters, Dominik Janzing, Bernhard Schölkopf
Causal inference uses observations to infer the causal structure of the data generating system. We study a class of functional models that we call Time Series Models with Independe…
Identifying confounders using additive noise models
Dominik Janzing, Jonas Peters, Joris Mooij +1
We propose a method for inferring the existence of a latent common cause ('confounder') of two observed random variables. The method assumes that the two effects of the confounder…
Identifiability of Gaussian structural equation models with equal error variances
Jonas Peters, Peter Bühlmann
We consider structural equation models in which variables can be written as a function of their parents and noise terms, which are assumed to be jointly independent. Corresponding…