7 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice
Tom Vermeire, Thibault Laugel, Xavier Renard +2
Explainability is becoming an important requirement for organizations that make use of automated decision-making due to regulatory initiatives and a shift in public awareness. Vari…
cs.HC2021★ 7 cited
Understanding Consumer Preferences for Explanations Generated by XAI Algorithms
Yanou Ramon, Tom Vermeire, Olivier Toubia +2
Explaining firm decisions made by algorithms in customer-facing applications is increasingly required by regulators and expected by customers. While the emerging field of Explainab…
cs.LG2020★ 4 cited
Explainable Image Classification with Evidence Counterfactual
Tom Vermeire, David Martens
The complexity of state-of-the-art modeling techniques for image classification impedes the ability to explain model predictions in an interpretable way. Existing explanation metho…