FKRSBM achieves superior distributional alignment and improved downstream classification when harmonizing PI-2620 tau PET data to the AV-1451 domain compared to ComBat, CycleGAN, and diffusion baselines.
Schrödinger bridge for generative ai: Soft-constrained formulation and convergence analysis
2 Pith papers cite this work. Polarity classification is still indexing.
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W-Flow compresses a Wasserstein gradient flow defined via Sinkhorn divergence into a single-step neural generator, reporting 1.29 FID on ImageNet 256x256 with improved mode coverage.
citing papers explorer
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Feynman Kac Reweighted Schr\"odinger Bridge Matching for Surface-Based Tau PET Harmonization
FKRSBM achieves superior distributional alignment and improved downstream classification when harmonizing PI-2620 tau PET data to the AV-1451 domain compared to ComBat, CycleGAN, and diffusion baselines.
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One-Step Generative Modeling via Wasserstein Gradient Flows
W-Flow compresses a Wasserstein gradient flow defined via Sinkhorn divergence into a single-step neural generator, reporting 1.29 FID on ImageNet 256x256 with improved mode coverage.