54 citations · 57 across the 3 of their papers we have counts for
4 papers
Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI
Adam White, Margarita Saranti, Artur d'Avila Garcez +3
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very…
Counterfactual Instances Explain Little
Adam White, Artur d'Avila Garcez
In many applications, it is important to be able to explain the decisions of machine learning systems. An increasingly popular approach has been to seek to provide \emph{counterfac…
Contrastive Counterfactual Visual Explanations With Overdetermination
Adam White, Kwun Ho Ngan, James Phelan +4
A novel explainable AI method called CLEAR Image is introduced in this paper. CLEAR Image is based on the view that a satisfactory explanation should be contrastive, counterfactual…
Measurable Counterfactual Local Explanations for Any Classifier
Adam White, Artur d'Avila Garcez
We propose a novel method for explaining the predictions of any classifier. In our approach, local explanations are expected to explain both the outcome of a prediction and how tha…