# Reparametrization Invariance in non-parametric Causal Discovery

@article{Jrgensen2020ReparametrizationII, title={Reparametrization Invariance in non-parametric Causal Discovery}, author={Martin J{\o}rgensen and S{\o}ren Hauberg}, journal={arXiv: Machine Learning}, year={2020} }

Causal discovery estimates the underlying physical process that generates the observed data: does X cause Y or does Y cause X? Current methodologies use structural conditions to turn the causal query into a statistical query, when only observational data is available. But what if these statistical queries are sensitive to causal invariants? This study investigates one such invariant: the causal relationship between X and Y is invariant to the marginal distributions of X and Y. We propose an…

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