3 papers
cs.CV2026
What is Missing? Explaining Neurons Activated by Absent Concepts
Robin Hesse, Simone Schaub-Meyer, Janina Hesse +2
Explainable artificial intelligence (XAI) aims to provide human-interpretable insights into the behavior of deep neural networks (DNNs), typically by estimating a simplified causal…
cs.CV2026
Beyond Accuracy: What Matters in Designing Well-Behaved Image Classification Models?
Robin Hesse, DoÄukan BaÄcı, Bernt Schiele +2
Deep learning has become an essential part of computer vision, with deep neural networks (DNNs) excelling in predictive performance. However, they often fall short in other critica…
cs.LG2025
Activation Subspaces for Out-of-Distribution Detection
BarıŠZöngür, Robin Hesse, Stefan Roth
To ensure the reliability of deep models in real-world applications, out-of-distribution (OOD) detection methods aim to distinguish samples close to the training distribution (in-d…