Explaining and visualizing black-box models through counterfactual paths

1 code implementation • 15 Jul 2023 • Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki, Anna Saranti, Andreas Holzinger, Przemyslaw Biecek

Explainable AI (XAI) is an increasingly important area of machine learning research, which aims to make black-box models transparent and interpretable.

counterfactual Explainable Artificial Intelligence (XAI) +2

Performance is not enough: the story told by a Rashomon quartet

1 code implementation • 26 Feb 2023 • Przemyslaw Biecek, Hubert Baniecki, Mateusz Krzyzinski, Dianne Cook

The usual goal of supervised learning is to find the best model, the one that optimizes a particular performance measure.