arXiv Machine Learning July 1, 2026 By Onkar Jadhav, Tim French, Matthew Rayson, Nicole L. Jones

Patch-PODiff-ViT: Structured Latent Diffusion with Patchwise POD for Super-Resolution and Uncertainty Quantification

Read the original on arXiv Machine Learning →

arXiv:2606. 31290v1 Announce Type: new Abstract: Diffusion models enable probabilistic super-resolution and conditional generation, but pixel-space methods are computationally expensive and learned latent spaces often lack interpretable uncertainty quantification.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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