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### Model/Pipeline/Scheduler description
Achieving faithful image-to-noise inversion with Denoising Diffusion models remains a challenge, particularly for more recent models trained to generate image…
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hi mahdibeit ,
1. Your proposed baseline is similar to CCVR[No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data]. Why don't make a comparison with it?
2. Cou…
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The idea is perhaps future-looking, but I'd like to bring it up for discussion.
## Motivations
* Reduce the GPU/NPU memory required for completing a use case (e.g. text2image).
* Reduce the mem…
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> [!NOTE]
> If you have a request to support a specific method, or would like to see priority of one of the listed methods, please open a separate issue, so it won't get buried in this thread. Base…
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# Welcome to JunYoung's blog | DDIM(Denoising Diffusion Implicit Models) 이해하기
Diffusion implicit modeling
[https://junia3.github.io/blog/ddim](https://junia3.github.io/blog/ddim)
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Hey John! Here's the curriculum that I've worked on in the past. It's a bit less focused on language models as a sole topic, and more on modern ML from a broad perspective.
- Essential Concepts of …
zmaas updated
3 months ago
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Hello,
I try to run this repository. But I had the following error when I train the model.
`
Traceback (most recent call last):
File "train_ddgan.py", line 609, in
init_processes(0, size…
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Hello, interesting work!
Or use JPEG for noisy images and then use Denoising Diffusion to restore[2]?
[1] Nie W, Guo B, Huang Y, et al. Diffusion models for adversarial purification. ICML 2022.
[…
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### Model/Pipeline/Scheduler description
Text-to-video diffusion models enable the generation of high-quality videos given text prompts, making it easy to create diverse and individual content. How…
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https://sunlin-ai.github.io/2022/05/29/DDIM.html
关于 DDIM 的论文理解