1 citations · 1 across the 7 of their papers we have counts for
7 papers
When Multi-Sensor Fusion Fails to Generalize: Cattle Posture Classification Under Animal-Level and Temporal Distribution Shift
Leutrim Uka, Severino Pinto, Gundula Hoffmann +1
Automated cattle posture-classification systems frequently report near-perfect accuracy, yet their robustness under realistic deployment conditions remains largely unknown. In part…
Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
Georgii Mikriukov, Grégoire Montavon, Marina M. -C. Höhne
Post-hoc explanation methods are widely used to interpret black-box predictions, but their generation is often computationally expensive and their reliability is not guaranteed. We…
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather
Philine L. Bommer, Marlene Kretschmer, Fiona R. Spuler +2
Predictions on subseasonal-to-seasonal (S2S) timescales--ranging from two weeks to two month--are crucial for early warning systems but remain challenging owing to chaos in the cli…
Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution
Carlos Eiras-Franco, Anna Hedström, Marina M. -C. Höhne
Obtaining high-quality explanations of a model's output enables developers to identify and correct biases, align the system's behavior with human values, and ensure ethical complia…
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation
Kristoffer Wickstrøm, Marina Marie-Claire Höhne, Anna Hedström
The lack of ground truth explanation labels is a fundamental challenge for quantitative evaluation in explainable artificial intelligence (XAI). This challenge becomes especially p…
A Fresh Look at Sanity Checks for Saliency Maps
Anna Hedström, Leander Weber, Sebastian Lapuschkin +1
The Model Parameter Randomisation Test (MPRT) is highly recognised in the eXplainable Artificial Intelligence (XAI) community due to its fundamental evaluative criterion: explanati…