{"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/a-cnn-adapted-to-time-series-for-the","title":"A CNN adapted to time series for the classification of Supernovae","arxiv_id":"1901.00461","date":"2019-01-02","proceeding":null,"authors":["Anthony Brunel","Johanna Pasquet","Jérôme Pasquet","Nancy Rodriguez","Frédéric Comby","Dominique Fouchez","Marc Chaumont"],"abstract":"Cosmologists are facing the problem of the analysis of a huge quantity of\ndata when observing the sky. The methods used in cosmology are, for the most of\nthem, relying on astrophysical models, and thus, for the classification, they\nusually use a machine learning approach in two-steps, which consists in, first,\nextracting features, and second, using a classifier. In this paper, we are\nspecifically studying the supernovae phenomenon and especially the binary\nclassification \"I.a supernovae versus not-I.a supernovae\". We present two\nConvolutional Neural Networks (CNNs) defeating the current state-of-the-art.\nThe first one is adapted to time series and thus to the treatment of supernovae\nlight-curves. The second one is based on a Siamese CNN and is suited to the\nnature of data, i.e. their sparsity and their weak quantity (small learning\ndatabase).","url_abs":"http://arxiv.org/abs/1901.00461v1","url_pdf":"http://arxiv.org/pdf/1901.00461v1.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":"a-cnn-adapted-to-time-series-for-the","repo_url":"https://github.com/Anzzy30/SupernovaeClassification","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"binary-classification","task_name":"Binary Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}