13 citations · 18 across the 3 of their papers we have counts for
3 papers · 1 filter
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier
Sumedha Singla, Nihal Murali, Forough Arabshahi +2
A highly accurate but overconfident model is ill-suited for deployment in critical applications such as healthcare and autonomous driving. The classification outcome should reflect…
Using Causal Analysis for Conceptual Deep Learning Explanation
Sumedha Singla, Stephen Wallace, Sofia Triantafillou +1
Model explainability is essential for the creation of trustworthy Machine Learning models in healthcare. An ideal explanation resembles the decision-making process of a domain expe…
Explanation by Progressive Exaggeration
Sumedha Singla, Brian Pollack, Junxiang Chen +1
As machine learning methods see greater adoption and implementation in high stakes applications such as medical image diagnosis, the need for model interpretability and explanation…