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cs.LG2024
Algebraic Adversarial Attacks on Integrated Gradients
Lachlan Simpson, Federico Costanza, Kyle Millar +3
Adversarial attacks on explainability models have drastic consequences when explanations are used to understand the reasoning of neural networks in safety critical systems. Path me…
cs.LG2024
Probabilistic Lipschitzness and the Stable Rank for Comparing Explanation Models
Lachlan Simpson, Kyle Millar, Adriel Cheng +2
Explainability models are now prevalent within machine learning to address the black-box nature of neural networks. The question now is which explainability model is most effective…