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Latent Annealed Posterior Sampling with a Variance-Preserving Bridge for Sparsely Observed Random Fields

Lei, Jiankun et al.
arXiv (All) · Papers
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machine-learning
Posterior inference for random fields from sparse observations presents two major challenges: accurately characterizing complex spatial uncertainty and preventing conditional sampling costs from growing substantially as the spatial grid is refined. To address these challenges, we propose latent anne
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