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cs.LG2024
GLEAMS: Bridging the Gap Between Local and Global Explanations
Giorgio Visani, Vincenzo Stanzione, Damien Garreau
The explainability of machine learning algorithms is crucial, and numerous methods have emerged recently. Local, post-hoc methods assign an attribution score to each feature, indic…
cs.CV2024
CAM-Based Methods Can See through Walls
Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
CAM-based methods are widely-used post-hoc interpretability method that produce a saliency map to explain the decision of an image classification model. The saliency map highlights…