{"url":"/task/sequential-bayesian-inference","name":"Sequential Bayesian Inference","slug":"sequential-bayesian-inference","description_markdown":"Also known as Bayesian filtering or [recursive Bayesian estimation](https://en.wikipedia.org/wiki/Recursive_Bayesian_estimation), this task aims to perform inference on latent state-space models.","categories":[{"name":"Time Series","url":"/area/time-series"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":20,"papers_with_code":11,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":11,"of":11,"tagged_in_all":20,"items":[{"url":"/paper/meta-particle-flow-for-sequential-bayesian","title":"Particle Flow Bayes' Rule","date":"2019-02-02","arxiv_id":"1902.00640","repositories_listed":2,"syntology":{"n":8,"n_ran":1,"n_unverified":7,"n_pointer_only":0}},{"url":"/paper/bayesian-online-natural-gradient-bong","title":"Bayesian Online Natural Gradient (BONG)","date":"2024-05-30","arxiv_id":"2405.19681","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/continual-learning-via-sequential-function","title":"Continual Learning via Sequential Function-Space Variational Inference","date":"2023-12-28","arxiv_id":"2312.17210","repositories_listed":1,"syntology":{"n":12,"n_ran":8,"n_unverified":4,"n_pointer_only":0}},{"url":"/paper/learning-differentiable-particle-filter-on","title":"Learning Differentiable Particle Filter on the Fly","date":"2023-12-10","arxiv_id":"2312.05955","repositories_listed":1,"syntology":null},{"url":"/paper/a-digital-twin-framework-for-civil","title":"A digital twin framework for civil engineering structures","date":"2023-08-02","arxiv_id":"2308.01445","repositories_listed":1,"syntology":null},{"url":"/paper/on-sequential-bayesian-inference-for","title":"On Sequential Bayesian Inference for Continual Learning","date":"2023-01-04","arxiv_id":"2301.01828","repositories_listed":1,"syntology":null},{"url":"/paper/discriminative-bayesian-filtering-lends","title":"Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functions","date":"2021-04-27","arxiv_id":"2104.12949","repositories_listed":1,"syntology":null},{"url":"/paper/the-discriminative-kalman-filter-for-bayesian","title":"The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/functional-regularisation-for-continual","title":"Functional Regularisation for Continual Learning with Gaussian Processes","date":"2019-01-31","arxiv_id":"1901.11356","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/a-discriminative-approach-to-bayesian","title":"A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding","date":"2018-07-17","arxiv_id":"1807.06173","repositories_listed":1,"syntology":null},{"url":"/paper/kernel-embedding-of-maps-for-sequential","title":"Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter","date":"2018-05-29","arxiv_id":"1805.11380","repositories_listed":1,"syntology":null}],"syntology_records":4,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}