12 citations · 19 across the 4 of their papers we have counts for
3 papers · 1 filter
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…
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations
Rachana Balasubramanian, Samuel Sharpe, Brian Barr +2
In the environment of fair lending laws and the General Data Protection Regulation (GDPR), the ability to explain a model's prediction is of paramount importance. High quality expl…
Towards Ground Truth Explainability on Tabular Data
Brian Barr, Ke Xu, Claudio Silva +4
In data science, there is a long history of using synthetic data for method development, feature selection and feature engineering. Our current interest in synthetic data comes fro…