Quantitative Attributions with Counterfactuals

Attention

Check out the new pre-print on biorxiv: Quantitative Attributions with Counterfactuals!

QuAC is a tool for understanding the sometimes subtle differences between classes of images, by questioning a classifier’s decisions. The method generates counterfactual images: making slight changes in an image to change its clasification. The counterfactuals in QuAC have localized changes, and are quantitatively scored to determine how well they describe the classifier’s decision.

Get started with installation, then check out the tutorials to run each step of the QuAC pipeline on an example dataset.

Unsure whether QuAC is right for your dataset? Check out the examples to see how it has been used already!

• Installation
• Example gallery
  • Fictus Aggregatum synthetic cells
  • Drosophila melanogaster synapses
  • Fly identity
• Tutorials
  • What even is QuAC?
  • The classifier
  • The conversion network
  • Attribution and evaluation
  • Visualizing results
  • Table of Contents