{"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/numerical-calabi-yau-metrics-from-holomorphic","title":"Numerical Calabi-Yau metrics from holomorphic networks","arxiv_id":"2012.04797","date":"2020-12-09","proceeding":null,"authors":["Michael R. Douglas","Subramanian Lakshminarasimhan","Yidi Qi"],"abstract":"We propose machine learning inspired methods for computing numerical Calabi-Yau (Ricci flat K\\\"ahler) metrics, and implement them using Tensorflow/Keras. We compare them with previous work, and find that they are far more accurate for manifolds with little or no symmetry. We also discuss issues such as overparameterization and choice of optimization methods.","url_abs":"https://arxiv.org/abs/2012.04797v2","url_pdf":"https://arxiv.org/pdf/2012.04797v2.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"numerical-calabi-yau-metrics-from-holomorphic","repo_url":"https://github.com/yidiq7/MLGeometry","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2012.04797","atlas_url":"https://app.syntology.ai/?focus=2012.04797","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}