{"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/unbiased-filtering-of-a-class-of-partially","title":"Unbiased Filtering of a Class of Partially Observed Diffusions","arxiv_id":"2002.03747","date":"2020-02-10","proceeding":null,"authors":["Ajay Jasra","Kody Law","Fangyuan Yu"],"abstract":"In this article we consider a Monte Carlo-based method to filter partially observed diffusions observed at regular and discrete times. Given access only to Euler discretizations of the diffusion process, we present a new procedure which can return online estimates of the filtering distribution with no discretization bias and finite variance. Our approach is based upon a novel double application of the randomization methods of Rhee & Glynn (2015) along with the multilevel particle filter (MLPF) approach of Jasra et al (2017). A numerical comparison of our new approach with the MLPF, on a single processor, shows that similar errors are possible for a mild increase in computational cost. However, the new method scales strongly to arbitrarily many processors.","url_abs":"http://arxiv.org/abs/2002.03747v2","url_pdf":"http://arxiv.org/pdf/2002.03747v2.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":"unbiased-filtering-of-a-class-of-partially","repo_url":"https://github.com/fangyuan-ksgk/Parallel-Particle-Filter-HPC-","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"unbiased-filtering-of-a-class-of-partially","repo_url":"https://github.com/fangyuan-ksgk/Unbiased-Particle-Filter-HPC-","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"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}