Code for "Accelerating Bayesian computation with deep generative samplers by Multilevel Monte Carlo" Haji-Ali et. al. (2024) adapted from https://github.com/yang-song/score_sde_pytorch associated to

References

@inproceedings{
  song2021scorebased,
  title={Score-Based Generative Modeling through Stochastic Differential Equations},
  author={Yang Song and Jascha Sohl-Dickstein and Diederik P Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole},
  booktitle={International Conference on Learning Representations},
  year={2021},
  url={https://openreview.net/forum?id=PxTIG12RRHS}
}

Used under Apache-2.0 license.

Make sure that you download CIFAR10 to the appropriate directory (see main.py) and then run e.g.

python main.py --workdir exp/checkpoints/cifar10_ddpmpp_continuous --acc 0.0086 --config configs/vp/cifar10_ddpmpp_continuous.py --eval_folder exp/eval/cifar10DenoisingSecondmoment_0.8 --MLMCsampler EXPINT --probflow=False --conditional=True --payoff secondmoment --conditional_noise .8