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Opportunities and limitations of explaining quantum machine learning
Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon +3
A common trait of many machine learning models is that it is often difficult to understand and explain what caused the model to produce the given output. While the explainability o…
Analyzing Atomic Interactions in Molecules as Learned by Neural Networks
Malte Esders, Thomas Schnake, Jonas Lederer +4
While machine learning (ML) models have been able to achieve unprecedented accuracies across various prediction tasks in quantum chemistry, it is now apparent that accuracy on a te…
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
Thomas Schnake, Farnoush Rezaei Jafari, Jonas Lederer +5
Explainable Artificial Intelligence (XAI) plays a crucial role in fostering transparency and trust in AI systems, where traditional XAI approaches typically offer one level of abst…
The Clever Hans Effect in Unsupervised Learning
Jacob Kauffmann, Jonas Dippel, Lukas Ruff +3
Unsupervised learning has become an essential building block of AI systems. The representations it produces, e.g. in foundation models, are critical to a wide variety of downstream…
MambaLRP: Explaining Selective State Space Sequence Models
Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller +1
Recent sequence modeling approaches using selective state space sequence models, referred to as Mamba models, have seen a surge of interest. These models allow efficient processing…
XpertAI: uncovering regression model strategies for sub-manifolds
Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon
In recent years, Explainable AI (XAI) methods have facilitated profound validation and knowledge extraction from ML models. While extensively studied for classification, few XAI so…
Explaining Predictive Uncertainty by Exposing Second-Order Effects
Florian Bley, Sebastian Lapuschkin, Wojciech Samek +1
Explainable AI has brought transparency into complex ML blackboxes, enabling, in particular, to identify which features these models use for their predictions. So far, the question…