relax-xai 0.0.1

RELAX: a framework for explainability in representation learning.

RELAX: Representation Learning Explainability

• Currently undergoing major changes to repository

• This repository contains code for RELAX, a framework for representation learning explainability. RELAX is based on perturbation-based explainability and work by measuring the change in the representation space as parts of the input are masked out.

• When should you use RELAX? If your output is a vector representation and you have no label information.

• More information can be found in the paper: Representation Learning Explainability (Wickstrøm et al., 2023), (Wickstrøm et al., 2022)

• You can see RELAX used in practice in medical image retrieval in the paper: A clinically motivated self-supervised approach for content-based image retrieval of CT liver images (Wickstrøm et al., 2023), (Wickstrøm et al., 2022)

Citation

If you find RELAX interesting and use it in your research, use the following Bibtex annotation to cite:

@article{wickstrom2023relax,
  author  = {Wickstr\o{}m, Kristoffer K. and Trosten, Daniel J. and L\o{}kse, Sigurd and Boubekki, Ahc\`{e}ne and Mikalsen, Karl \o{}yvind and Kampffmeyer, Michael C. and Jenssen, Robert},
  title   = {RELAX: Representation Learning Explainability},
  journal = {International Journal of Computer Vision},
  year    = {2023},
  volume  = {131},
  number  = {6},
  pages   = {1584–1610},
  url     = {https://doi.org/10.1007/s11263-023-01773-2}
}