{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/removing-systematic-errors-for-exoplanet","title":"Removing systematic errors for exoplanet search via latent causes","arxiv_id":"1505.03036","date":"2015-05-12","proceeding":null,"authors":["Bernhard Schölkopf","David W. Hogg","Dun Wang","Daniel Foreman-Mackey","Dominik Janzing","Carl-Johann Simon-Gabriel","Jonas Peters"],"abstract":"We describe a method for removing the effect of confounders in order to\nreconstruct a latent quantity of interest. The method, referred to as\nhalf-sibling regression, is inspired by recent work in causal inference using\nadditive noise models. We provide a theoretical justification and illustrate\nthe potential of the method in a challenging astronomy application.","url_abs":"http://arxiv.org/abs/1505.03036v1","url_pdf":"http://arxiv.org/pdf/1505.03036v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"removing-systematic-errors-for-exoplanet","repo_url":"https://github.com/jvc2688/KeplerPixelModel","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"astronomy","task_name":"Astronomy"},{"task_slug":"causal-inference","task_name":"Causal Inference"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"causal-inference","method_name":"Causal inference"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}