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Inductive Moment Matching (IMM) offers a stable, efficient generative model for one- or few-step sampling, outperforming diffusion models and achieving state-of-the-art results on ImageNet and CIFAR-10.
https://arxiv.org/abs//2503.07565
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
5
33 ratings
Inductive Moment Matching (IMM) offers a stable, efficient generative model for one- or few-step sampling, outperforming diffusion models and achieving state-of-the-art results on ImageNet and CIFAR-10.
https://arxiv.org/abs//2503.07565
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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