3 papers
cs.LG2026
BREAD: Baseline-Referenced Explanations for Anomaly Diagnosis
Jiaqi Qiu, Rob Goedhart, Jannis Kurtz +1
Artificial Intelligence (AI)-based prospective anomaly detection methods are increasingly deployed in high-dimensional and nonlinear settings. Among these approaches, AI-based stat…
cs.HC2026
Improving understanding and trust in AI: How users benefit from interval-based counterfactual explanations
Tabea E. Röber, Paul Festor, Rob Goedhart +2
Experimental user studies evaluating the effectiveness of different subtypes of post-hoc explanations for black-box models are largely nonexistent. Therefore, the aim of this study…
cs.LG2025
Clinicians' Voice: Fundamental Considerations for XAI in Healthcare
T. E. Röber, R. Goedhart, S. İ. Birbil
Explainable AI (XAI) holds the promise of advancing the implementation and adoption of AI-based tools in practice, especially in high-stakes environments like healthcare. However,…