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The Ethereal
Removing systematic errors for exoplanet search via latent causes
May 12, 2015 ยท Declared Dead ยท ๐ International Conference on Machine Learning
"No code URL or promise found in abstract"
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Authors
Bernhard Schรถlkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
arXiv ID
1505.03036
Category
stat.ML: Machine Learning (Stat)
Cross-listed
astro-ph.EP,
astro-ph.IM,
cs.LG
Citations
11
Venue
International Conference on Machine Learning
Last Checked
4 months ago
Abstract
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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