Analysis of Classifier-Free Guidance Weight Schedulers
Classifier-Free Guidance (CFG) enhances the quality and condition adherence of text-toimage diffusion models. It operates by combining the conditional and unconditional predictions using a fixed weight. However, recent works vary the weights throughout the diffusion process, reporting superior resul...
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| Published in: | Transactions on Machine Learning Research Journal |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
[Amherst Massachusetts]: OpenReview.net, 2022
2024
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| Subjects: | |
| ISSN: | 2835-8856 |
| Online Access: | Get full text |
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