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Multi-point Bayesian active learning line sampling for rare event estimation
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DOI：10.1016/j.ress.2025.112136.png)
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Abstract
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• Line sampling is treated from a multi-point Bayesian active learning perspective. • A fair metric bounding the variance of failure probability is derived. • A multi-point look-ahead learning function is analytically deduced. • Single- and batch-enrichment are conducted in a goal-consistent manner.
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