Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning. - Richard Tomsett; Amy Widdicombe; Tianwei Xing; Supriyo Chakraborty; Simon Julier; Prudhvi Gurram; Raghuveer M. Rao; Mani B. Srivastava (FUSION, 2018)

NeuroMask: Explaining Predictions of Deep Neural Networks through Mask Learning. - Moustafa Alzantot; Amy Widdicombe; Simon Julier; Mani B. Srivastava (SMARTCOMP, 2019)

Gradient-Based Interpretability Methods and Binarized Neural Networks. - Amy Widdicombe; Simon J. Julier (CoRR, 2021)

The Effect of Model Size on LLM Post-hoc Explainability via LIME. - Henning Heyen; Amy Widdicombe; Noah Y. Siegel; María Pérez-Ortiz 001; Philip C. Treleaven (CoRR, 2024)