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Sequential multiple importance sampling for multi-modal Bayesian inference
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AI
DOI：10.1016/j.ymssp.2025.113788.png)
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Abstract
En 中文
• Propose a new form of proposal distribution bridging prior and posterior distributions. • Proposal distributions are determined sequentially and adaptively from samples. • Proposal distributions allow easier transition between isolated modes. • Improve accuracy in high-dimensional and multi-modal Bayesian inference. • Compared with two advanced algorithms on benchmarks and model updating.
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8.9
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1.3W
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6.6W
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