Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching

This code belongs to the paper 'Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching' available at https://arxiv.org/abs/2403.18705 [1]. Please cite the paper, if you use our code.

It contains implementations for the experiments of Section 8. For questions or bug reports contact chemseddine@math.tu-berlin.de or hagemann@math.tu-berlin.de.

REQUIREMENTS

The code requires several Python packages. The specific requirements are given in requirements.txt

References

[1] J. Chemseddine, P. Hagemann, C. Wald, G. Steidl. Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching.

CITATION

@article{CHWS2024,
      title={Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching}, 
      author={Jannis Chemseddine and Paul Hagemann and Christian Wald and Gabriele Steidl},
      journal={arXiv preprint arXiv:2403.18705}
}