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The kernels exploit properties of ensembles of light transport paths, which are distributed according to the lighting in the scene, and utilize this information to make informed decisions for guiding local path sampling. Critically, our approach does not require caching distributions in world space, saving time and memory, yet it is able to make guided sampling decisions based on whole paths. We show how this can be implemented efficiently by organizing the paths in each ensemble and designing transition kernels for MCMC rendering based on a carefully chosen subset of paths from the ensemble. This algorithm is easy to parallelize and leads to improvements in variance when rendering a variety of scenes.\n          <\/jats:p>","DOI":"10.1145\/3472294","type":"journal-article","created":{"date-parts":[[2021,12,20]],"date-time":"2021-12-20T21:21:44Z","timestamp":1640035304000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Ensemble Metropolis Light Transport"],"prefix":"10.1145","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4669-0417","authenticated-orcid":false,"given":"Thomas","family":"Bashford-Rogers","sequence":"first","affiliation":[{"name":"University of the West of England, Coldharbour Ln, Bristol BS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4466-1129","authenticated-orcid":false,"given":"Lu\u00eds Paulo","family":"Santos","sequence":"additional","affiliation":[{"name":"Universidade do Minho\/INESC TEC, Braga, Portugal"}]},{"given":"Demetris","family":"Marnerides","sequence":"additional","affiliation":[{"name":"University of Warwick, Coventry, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2982-5199","authenticated-orcid":false,"given":"Kurt","family":"Debattista","sequence":"additional","affiliation":[{"name":"University of Warwick, Coventry, UK"}]}],"member":"320","published-online":{"date-parts":[[2021,12,20]]},"reference":[{"volume-title":"Computer Graphics Forum","author":"Bako Steve","key":"e_1_2_2_1_1","unstructured":"Steve Bako , Mark Meyer , Tony DeRose , and Pradeep Sen . 2019. 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