14 citations · 50 across the 12 of their papers we have counts for
4 papers · 1 filter
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence
Isha Hameed, Samuel Sharpe, Daniel Barcklow +5
Explainable artificial intelligence (XAI) methods lack ground truth. In its place, method developers have relied on axioms to determine desirable properties for their explanations'…
Calibrate: Interactive Analysis of Probabilistic Model Output
Peter Xenopoulos, Joao Rulff, Luis Gustavo Nonato +2
Analyzing classification model performance is a crucial task for machine learning practitioners. While practitioners often use count-based metrics derived from confusion matrices,…
Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets
Jun Yuan, Brian Barr, Kyle Overton +1
One of the potential solutions for model interpretation is to train a surrogate model: a more transparent model that approximates the behavior of the model to be explained. Typical…
Topological Representations of Local Explanations
Peter Xenopoulos, Gromit Chan, Harish Doraiswamy +3
Local explainability methods -- those which seek to generate an explanation for each prediction -- are becoming increasingly prevalent due to the need for practitioners to rational…