23 citations · 50 across the 5 of their papers we have counts for
5 papers
Approximating Score-based Explanation Techniques Using Conformal Regression
Amr Alkhatib, Henrik Boström, Sofiane Ennadir +1
Score-based explainable machine-learning techniques are often used to understand the logic behind black-box models. However, such explanation techniques are often computationally e…
Calibrated Explanations for Regression
Tuwe Löfström, Helena Löfström, Ulf Johansson +2
Artificial Intelligence (AI) is often an integral part of modern decision support systems. The best-performing predictive models used in AI-based decision support systems lack tran…
Well-Calibrated Probabilistic Predictive Maintenance using Venn-Abers
Ulf Johansson, Tuwe Löfström, Cecilia Sönströd
When using machine learning for fault detection, a common problem is the fact that most data sets are very unbalanced, with the minority class (a fault) being the interesting one.…
Calibrated Explanations: with Uncertainty Information and Counterfactuals
Helena Lofstrom, Tuwe Lofstrom, Ulf Johansson +1
While local explanations for AI models can offer insights into individual predictions, such as feature importance, they are plagued by issues like instability. The unreliability of…
A Meta Survey of Quality Evaluation Criteria in Explanation Methods
Helena Löfström, Karl Hammar, Ulf Johansson
Explanation methods and their evaluation have become a significant issue in explainable artificial intelligence (XAI) due to the recent surge of opaque AI models in decision suppor…