AI RESEARCH
Efficient Weighted Sampling via Score-based Generative Models
arXiv CS.AI
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ArXi:2502.04646v2 Announce Type: replace-cross Weighted sampling -- sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function -- is a fundamental technique with wide-ranging applications in variance reduction, biased sampling, data augmentation, and more. Leveraging the increasing availability of pretrained score-based generative models (SGMs), we propose a