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Uncertainty attributions

This is the official tensorflow implementation of the following manuscript:

Perez, I., Skalski, P., Barns-Graham, A., Wong, J. and Sutton, D. (2022) Attribution of Predictive Uncertainties in Classification Models, 38th Conference on Uncertainty in Artificial Intelligence (UAI), Eindhoven, Netherlands, 2022.

OpenReview link available here.

Contact: iker [dot] perez [at] featurespace [dot] co [dot] uk

Running the code

For the scripts to work correctly, you need to install the uncertainty_library and necessary dependencies. We recommend to do that by running

$ pip install .

in a virtual environment with python 3.8.

The scripts folder contains python scripts to train the models and reproduce results for the MNIST, FashionMNIST and CelebA datasets.