12 citations · 13 across the 3 of their papers we have counts for
3 papers
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,…
Counterfactual Explanations via Latent Space Projection and Interpolation
Brian Barr, Matthew R. Harrington, Samuel Sharpe +1
Counterfactual explanations represent the minimal change to a data sample that alters its predicted classification, typically from an unfavorable initial class to a desired target…