English(EN) Dual-space posterior sampling for Bayesian inference in constrained inverse problems

新贝叶斯推断方法解决约束逆问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-07 04:00

研究人员开发了一种新颖的贝叶斯推断方法，用于解决受偏微分方程约束的逆问题。该方法在最近的一篇论文中有所介绍，它使用增强拉格朗日公式在双空间中对后验分布进行采样。该方法将交替方向乘子法 (ADMM) 与 Stein 变分梯度下降法 (SVGD) 相结合，以逐步强制执行物理约束，例如全波形反演 (FWI) 中的波动方程。该技术已在包括 Marmousi II 数据集在内的基准问题上得到验证，证明了其生成物理上一致的不确定性估计的能力。 AI

排序理由这是一篇研究论文，详细介绍了一种新的贝叶斯推断方法。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv stat.ML 阅读 →

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arXiv stat.ML TIER_1 English(EN) · Ali Siahkoohi, Kamal Aghazade, Ali Gholami · 2026-08-07 04:00

面向约束逆问题的贝叶斯推断的双空间后验采样

arXiv:2603.00393v2 Announce Type: replace-cross Abstract: Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniqueness. A prominent example is full waveform inversion (FWI), which estimates Earth…

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面向约束逆问题的贝叶斯推断的双空间后验采样

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