Search Results for author: Céline Budding

Found 3 papers, 3 papers with code

Benchmark data to study the influence of pre-training on explanation performance in MR image classification

1 code implementation • 21 Jun 2023 • Marta Oliveira, Rick Wilming, Benedict Clark, Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe

Here, we propose a benchmark dataset that allows for quantifying explanation performance in a realistic magnetic resonance imaging (MRI) classification task.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2

Paper
Code

Evaluating saliency methods on artificial data with different background types

1 code implementation • 9 Dec 2021 • Céline Budding, Fabian Eitel, Kerstin Ritter, Stefan Haufe

Over the last years, many 'explainable artificial intelligence' (xAI) approaches have been developed, but these have not always been objectively evaluated.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Paper
Code

Scrutinizing XAI using linear ground-truth data with suppressor variables

1 code implementation • 14 Nov 2021 • Rick Wilming, Céline Budding, Klaus-Robert Müller, Stefan Haufe

It has been demonstrated that some saliency methods can highlight features that have no statistical association with the prediction target (suppressor variables).

Explainable Artificial Intelligence (XAI) Feature Importance

Paper
Code

Cannot find the paper you are looking for? You can Submit a new open access paper.