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.
Visual autoregressive modeling: Scalable image generation via next-scale prediction.NeurIPS, 37:84839–84865
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