{"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/data-driven-computing-with-noisy-material","title":"Data Driven Computing with Noisy Material Data Sets","arxiv_id":null,"date":"2017-11-01","proceeding":"Computer Methods in Applied Mechanics and Engineering 2017 11","authors":["T.Kirchdoerfer","M.Ortiz"],"abstract":"We formulate a Data Driven Computing paradigm, termed max-ent Data Driven Computing, that generalizes distance-minimizing Data Driven Computing and is robust with respect to outliers. Robustness is achieved by means of clustering analysis. Specifically, we assign data points a variable relevance depending on distance to the solution and on maximum-entropy estimation. The resulting scheme consists of the minimization of a suitably-defined free energy over phase space subject to compatibility and equilibrium constraints. Distance-minimizing Data Driven schemes are recovered in the limit of zero temperature. We present selected numerical tests that establish the convergence properties of the max-ent Data Driven solvers and solutions.","url_abs":"https://www.sciencedirect.com/science/article/pii/S0045782517304012","url_pdf":"https://www.sciencedirect.com/science/article/pii/S0045782517304012","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":[],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"stress-strain-relation","task_name":"Stress-Strain Relation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/stress-strain-relation-on-non-linear","task":"Stress-Strain Relation","dataset":"Non-Linear Elasticity Benchmark","model":"NLP","rank_in_archive_order":3,"of":4,"metrics":{"Time (ms)":"13.8"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}