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DTSTAMP:20260805T205602Z
LOCATION:Room 408 A
DTSTART;TZID=America/Los_Angeles:20260721T142000
DTEND;TZID=America/Los_Angeles:20260721T143000
UID:siggraph_SIGGRAPH 2026_sess131_papers_166@linklings.com
SUMMARY:Rao-Blackwellized Markov chain Monte Carlo Light Transport
DESCRIPTION:Sascha Holl (Max Planck Institute for Informatics, Saarland Un
 iversity); Gurprit Singh (Advanced Micro Devices (AMD)); and Hans-Peter Se
 idel (Max Planck Institute for Informatics)\n\nWe introduce a novel Rao-Bl
 ackwellization technique for variance reduction in Markov chain Monte Carl
 o light transport. We improve both Metropolis Light Transport and the curr
 ent state-of-the-art, Jump Restore Light Transport, consistently outperfor
 ming traditional variance reduction, accelerating convergence, and establi
 shing a new state-of-the-art in MCMC-based rendering under equal-time and 
 equal-sample evaluations.\n\nInterest Area: Research & Education\n\nKeywor
 d: Artificial Intelligence/Machine Learning, Modeling, Rendering, Simulati
 on\n\nRegistration Category: Full Conference Supporter, Full Conference\n\
 nSession Chair: Kun Xu (Tsinghua University)\n\n
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