3 papers
cs.LG2024
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models
Tuwe Löfström, Fatima Rabia Yapicioglu, Alessandra Stramiglio +2
This paper introduces Fast Calibrated Explanations, a method designed for generating rapid, uncertainty-aware explanations for machine learning models. By incorporating perturbatio…
cs.AI2024
Ensured: Explanations for Decreasing the Epistemic Uncertainty in Predictions
Helena Löfström, Tuwe Löfström, Johan Hallberg Szabadvary
This paper addresses a significant gap in explainable AI: the necessity of interpreting epistemic uncertainty in model explanations. Although current methods mainly focus on explai…
cs.AI2023
On the Definition of Appropriate Trust and the Tools that Come with it
Helena Löfström
Evaluating the efficiency of human-AI interactions is challenging, including subjective and objective quality aspects. With the focus on the human experience of the explanations, e…