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Official pytorch repository for "Diffusion Posterior Sampling for General Noisy Inverse Problems"

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Hi, I am trying to reproduce the results from the paper and I cannot find exactly which 1k images of the FFHQ and ImageNet dataset were used for the tables...

Hi, it's a nice job. I want to know that if this approach can be used on VE-SDE. Or in other words, why do you just use VP-SDE? Thanks

Thanks for your nice work. I tried this method on my own dataset and observed a phenomenon. During the testing phase, the performance of the model is affected by the...

I am trying to use the DDIM sampling method to decrease the number of sampling steps required. When I change the sampler to ddim in diffusion_config.yaml (and change nothing else)...

Hello, I am trying to reproduce phase retrieval results with Poisson noise. I have tried different rates for the noise but I never got a decent result, while results for...

Hello, thanks for publishing this paper and repo. I am curious about reproducing the results in the paper. I applied the Gaussian blur model to the first 1,000 images of...

Hi, we are trying to reproduce table 1 results, using the [https://www.kaggle.com/datasets/xhlulu/flickrfaceshq-dataset-nvidia-resized-256px](url) FFHQ256 dataset. So calculating FID for the reconstructed inpainting images (first 500 images of the dataset), we see...

It looks like every time the nonlinear blur operator is called, [a new random blur kernel is generated](https://github.com/DPS2022/diffusion-posterior-sampling/blob/effbde7325b22ce8dc3e2c06c160c021e743a12d/guided_diffusion/measurements.py#L196). When [calculating the guidance term](https://github.com/DPS2022/diffusion-posterior-sampling/blob/effbde7325b22ce8dc3e2c06c160c021e743a12d/guided_diffusion/condition_methods.py#L30), the kernel applied to the current posterior...

Hi, There are a few differences between the paper and this repository and it will be wonderful if you could clarify for me the reasons behind them: 1. The reported...