1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
ICON Decomposition: Auditing Deep Neural Networks with Multivariate Variance-based Concept-level Explanations
Roshan Prakash Rane, Marco Simnacher, Manuel Pfeuffer +7
Deep neural networks often exploit spurious associations, a failure known as shortcut learning. Auditing for shortcuts requires testing many candidate concepts, such as acquisition…
cs.LG2025★ 1 cited
Explainable AI Methods for Neuroimaging: Systematic Failures of Common Tools, the Need for Domain-Specific Validation, and a Proposal for Safe Application
Nys Tjade Siegel, James H. Cole, Mohamad Habes +3
Trustworthy interpretation of deep learning models is critical for neuroimaging applications, yet commonly used Explainable AI (XAI) methods lack rigorous validation, risking misin…