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Found 4 papers, 0 papers with code
The Anatomy of Adversarial Attacks: Concept-based XAI Dissection
Adversarial attacks (AAs) pose a significant threat to the reliability and robustness of deep neural networks.
GCPV: Guided Concept Projection Vectors for the Explainable Inspection of CNN Feature Spaces
The latter, though, is of particular interest for debugging, like finding and understanding outliers, learned notions of sub-concepts, and concept confusion.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces
These allow insights into both the flow and likeness of semantic information within CNN layers, and into the degree of their similarity between different network architectures.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+1
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability
The guiding use-case is a post-hoc explainability framework for object detection (OD) CNNs, towards which existing concept analysis (CA) methods are successfully adapted.
Dimensionality Reduction
Explainable artificial intelligence
+4
