5 papers
Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology
Mina Jamshidi Idaji, Julius Hense, Tom Neuhäuser +12
Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, where a large amount of patches from gigapixel whole slide images are aggregated…
Uncovering the Structure of Explanation Quality with Spectral Analysis
Johannes Maeß, Grégoire Montavon, Shinichi Nakajima +2
As machine learning models are increasingly considered for high-stakes domains, effective explanation methods are crucial to ensure that their prediction strategies are transparent…
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…
Synthesis of High-Resolution Load Profiles with Minimal Data
Thomas Schnake, David Bauer
For the estimation of a new energy supply system it is an important to have high-resolution energy load profile. Such a profile is in general either not present or very costly to o…