4 citations · 10 across the 5 of their papers we have counts for
5 papers
Contrastive Concept Importance: Explaining Pairwise Class Decisions Through Automatically Extracted Concept Representations
Roel Visser, Isaac Roberts, Barbara Hammer
Concept-based explanations are a prevalent way to explain the decisions of complex black-box methods through semantically meaningful, human interpretable concepts. To attribute the…
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust
Roel Visser, Tobias M. Peters, Ingrid Scharlau +1
A current concern in the field of Artificial Intelligence (AI) is to ensure the trustworthiness of AI systems. The development of explainability methods is one prominent way to add…
The Importance of Distrust in AI
Tobias M. Peters, Roel W. Visser
In recent years the use of Artificial Intelligence (AI) has become increasingly prevalent in a growing number of fields. As AI systems are being adopted in more high-stakes areas s…
Model Agnostic Local Explanations of Reject
André Artelt, Roel Visser, Barbara Hammer
The application of machine learning based decision making systems in safety critical areas requires reliable high certainty predictions. Reject options are a common way of ensuring…
Explaining Reject Options of Learning Vector Quantization Classifiers
André Artelt, Johannes Brinkrolf, Roel Visser +1
While machine learning models are usually assumed to always output a prediction, there also exist extensions in the form of reject options which allow the model to reject inputs wh…