{"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/nested-sequential-monte-carlo-methods","title":"Nested Sequential Monte Carlo Methods","arxiv_id":"1502.02536","date":"2015-02-09","proceeding":null,"authors":["Christian A. Naesseth","Fredrik Lindsten","Thomas B. Schön"],"abstract":"We propose nested sequential Monte Carlo (NSMC), a methodology to sample from\nsequences of probability distributions, even where the random variables are\nhigh-dimensional. NSMC generalises the SMC framework by requiring only\napproximate, properly weighted, samples from the SMC proposal distribution,\nwhile still resulting in a correct SMC algorithm. Furthermore, NSMC can in\nitself be used to produce such properly weighted samples. Consequently, one\nNSMC sampler can be used to construct an efficient high-dimensional proposal\ndistribution for another NSMC sampler, and this nesting of the algorithm can be\ndone to an arbitrary degree. This allows us to consider complex and\nhigh-dimensional models using SMC. We show results that motivate the efficacy\nof our approach on several filtering problems with dimensions in the order of\n100 to 1 000.","url_abs":"http://arxiv.org/abs/1502.02536v3","url_pdf":"http://arxiv.org/pdf/1502.02536v3.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":"nested-sequential-monte-carlo-methods","repo_url":"https://github.com/can-cs/nestedsmc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1502.02536","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1502.02536"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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