4 papers
Algebraic Adversarial Attacks on Explainability Models
Lachlan Simpson, Federico Costanza, Kyle Millar +3
Classical adversarial attacks are phrased as a constrained optimisation problem. Despite the efficacy of a constrained optimisation approach to adversarial attacks, one cannot trac…
Tangentially Aligned Integrated Gradients for User-Friendly Explanations
Lachlan Simpson, Federico Costanza, Kyle Millar +3
Integrated gradients is prevalent within machine learning to address the black-box problem of neural networks. The explanations given by integrated gradients depend on a choice of…
Riemannian Integrated Gradients: A Geometric View of Explainable AI
Federico Costanza, Lachlan Simpson
We introduce Riemannian Integrated Gradients (RIG); an extension of Integrated Gradients (IG) to Riemannian manifolds. We demonstrate that RIG restricts to IG when the Riemannian m…
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…