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Official repository for the Monte Carlo guided Diffusion for Bayesian linear inverse problems paper:

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MCG-Diff: Monte Carlo guided diffusion for Bayesian linear inverse problems

This repository contains the code of the algorithm proposed in https://arxiv.org/abs/2308.07983 and accepted for oral presentation at ICLR 2024.

This repository can be installed as a python package by running pip install -I . on the root folder of this git.

You can try this algorithm either with the available scripts in this project or in the benchopts, with comparison to other algorithms at https://github.com/gabrielvc/benchopts_inverse_problem_diffusion_prior/tree/master

Results using the hugging face models on CelebA

The following table was produced by running the scripts/hugging_faces_models.py with the configurations described below. The configuration for MCG DIFF is defined in scripts/configs/mcg_diff/default.yaml. Running this script took 3 minutes to generate each image, but this can be made faster by using parallelization.

Original image Observation Sample Sample Changes to config.yaml
image image image image seed = 32, task = deblur_2d
image image image image seed = 15, task = inpainting
image image image image seed = 10, task = sr

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Official repository for the Monte Carlo guided Diffusion for Bayesian linear inverse problems paper:

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