Semi-discrete Flow Matching produces terminal assignment regions that are topologically simple (open, simply connected, homeomorphic to the ball under assumption) yet geometrically distinct from optimal transport Laguerre cells, as they can be non-convex with curved boundaries.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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UPADNet applies phase-amplitude decomposition with novel LMMSE estimators inside an unrolled iterative algorithm, outperforming prior deblurring networks on GoPro, RealBlur, and COCO.
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Tessellations of Semi-Discrete Flow Matching
Semi-discrete Flow Matching produces terminal assignment regions that are topologically simple (open, simply connected, homeomorphic to the ball under assumption) yet geometrically distinct from optimal transport Laguerre cells, as they can be non-convex with curved boundaries.
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Leveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring
UPADNet applies phase-amplitude decomposition with novel LMMSE estimators inside an unrolled iterative algorithm, outperforming prior deblurring networks on GoPro, RealBlur, and COCO.