{"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/solving-linear-gaussian-bayesian-inverse","title":"Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo","arxiv_id":"2502.06379","date":"2025-02-10","proceeding":null,"authors":["Filip Ekström Kelvinius","Zheng Zhao","Fredrik Lindsten"],"abstract":"A recent line of research has exploited pre-trained generative diffusion models as priors for solving Bayesian inverse problems. We contribute to this research direction by designing a sequential Monte Carlo method for linear-Gaussian inverse problems which builds on \"decoupled diffusion\", where the generative process is designed such that larger updates to the sample are possible. The method is asymptotically exact and we demonstrate the effectiveness of our Decoupled Diffusion Sequential Monte Carlo (DDSMC) algorithm on both synthetic as well as protein and image data. Further, we demonstrate how the approach can be extended to discrete data.","url_abs":"https://arxiv.org/abs/2502.06379v2","url_pdf":"https://arxiv.org/pdf/2502.06379v2.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":"solving-linear-gaussian-bayesian-inverse","repo_url":"https://github.com/filipekstrm/ddsmc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[{"method_slug":"diffusion","method_name":"Diffusion"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2502.06379","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.06379"}},"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. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/filipekstrm/ddsmc","reach":null}],"summary":{"ran":1,"ran_draft_wrong":2,"ran_honours":1,"ran_fixture":1,"unverified":1},"by_repo_kind":{"official":{"samples":3,"ran":2,"repositories":1},"community":{"samples":3,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":3,"samples":[{"code_sha256_prefix":"695631f1f604071e","entry":"BatchedSMCHelper","repo":"filipekstrm/ddsmc","repo_kind":"official","path":"ddsmc/ddsmc_sampler.py","file_url":"https://github.com/filipekstrm/ddsmc/blob/HEAD/ddsmc/ddsmc_sampler.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"695631f1f604071e"}},{"code_sha256_prefix":"7b4ae256a4aab9ca","entry":"diag_gauss_logpdf","repo":"filipekstrm/ddsmc","repo_kind":"official","path":"ddsmc/ddsmc_sampler.py","file_url":"https://github.com/filipekstrm/ddsmc/blob/HEAD/ddsmc/ddsmc_sampler.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"7b4ae256a4aab9ca"}},{"code_sha256_prefix":"32aa054396114d07","entry":"norm","repo":"zhangbingliang2019/daps","repo_kind":"community","path":"posterior_sample.py","file_url":"https://github.com/zhangbingliang2019/daps/blob/HEAD/posterior_sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"32aa054396114d07"}},{"code_sha256_prefix":"a200f7f175d39914","entry":"resize","repo":"zhangbingliang2019/daps","repo_kind":"community","path":"posterior_sample.py","file_url":"https://github.com/zhangbingliang2019/daps/blob/HEAD/posterior_sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"a200f7f175d39914"}},{"code_sha256_prefix":"ca7d4c96a91ce87e","entry":"safe_dir","repo":"zhangbingliang2019/daps","repo_kind":"community","path":"posterior_sample.py","file_url":"https://github.com/zhangbingliang2019/daps/blob/HEAD/posterior_sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ca7d4c96a91ce87e"}},{"code_sha256_prefix":"cc3cb7dcc852608b","entry":"DDSMC","repo":"filipekstrm/ddsmc","repo_kind":"official","path":"ddsmc/ddsmc_sampler.py","file_url":"https://github.com/filipekstrm/ddsmc/blob/HEAD/ddsmc/ddsmc_sampler.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"cc3cb7dcc852608b"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}