4 citations · 9 across the 3 of their papers we have counts for
3 papers
Natural Example-Based Explainability: a Survey
Antonin Poché, Lucas Hervier, Mohamed-Chafik Bakkay
Explainable Artificial Intelligence (XAI) has become increasingly significant for improving the interpretability and trustworthiness of machine learning models. While saliency maps…
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis
Laurent Risser, Agustin Picard, Lucas Hervier +1
The problem of algorithmic bias in machine learning has gained a lot of attention in recent years due to its concrete and potentially hazardous implications in society. In much the…
Xplique: A Deep Learning Explainability Toolbox
Thomas Fel, Lucas Hervier, David Vigouroux +12
Today's most advanced machine-learning models are hardly scrutable. The key challenge for explainability methods is to help assisting researchers in opening up these black boxes, b…