Removing systematic errors for exoplanet search via latent causes
classification
📊 stat.ML
astro-ph.EPastro-ph.IMcs.LG
keywords
methodlatentremovingadditiveapplicationastronomycausalcauses
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We describe a method for removing the effect of confounders in order to reconstruct a latent quantity of interest. The method, referred to as half-sibling regression, is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification and illustrate the potential of the method in a challenging astronomy application.
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