๐Ÿฆ Twitter Post Details

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@giannis_daras

Announcing Ambient Diffusion Omni โ€” a framework that uses synthetic, low-quality, and out-of-distribution data to improve diffusion models. State-of-the-art ImageNet performance. A strong text-to-image results in just 2 days on 8 GPUs. Filtering โŒ Clever data use โœ… https://t.co/QPZzowf8rN

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                              "full_text": "@giannis_daras Me: *hearing 'Diffusion' in a new research paper*\n\nYou can say ใ•ใ‚ˆใชใ‚‰ to me reading it!",
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                              "full_text": "@giannis_daras Really nice work! After reading https://t.co/Jlt4HQ4U29, I am glad that theory informed some tangible advancements for diffusion model training.",
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                              "full_text": "@_AmilDravid Great paper indeed! I really enjoyed reading it. Glad that you liked our work ๐ŸŽ‰",
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                              "full_text": "@giannis_daras Hey @giannis_daras, Nice work!\nYou might be interested in our CVPR 2024 work where we reached a similar conclusion on dataset filtering. \"Donโ€™t drop your samples! Coherence-aware training benefits Conditional diffusion\".\nhttps://t.co/ILttmMhdwv",
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