The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability. Stephen Casper, Jieun Yun, Joonhyuk Baek, Yeseong Jung, Minhwan Kim, Kiwan Kwon, Saerom Park, Hayden Moore, David Shriver, Marissa Connor, Keltin Grimes, Angus Nicolson, Arush Tagade, Jessica Rumbelow, Hieu Minh Nguyen, Dylan Hadfield-Menell. SaTML 2024

[Paper] [Conference] [Competition] 


Developing an understanding of artificial intelligence lung nodule risk prediction using insights from the Brock model. Madhurima R Chetan, Nicholas Dowson, Noah Waterfield Price, Sarim Ather, Angus Nicolson, Fergus V Gleeson. European Radiology 2022.


Excited-state dynamics of molecules with classically driven trajectories and Gaussians. Lea M Ibele, Angus Nicolson, Basile FE Curchod. Molecular Physics 2020. 



Sparse Explanations for Gestational Age Prediction in Fetal Brain Ultrasound. Angus Nicolson, Yarin Gal, Alison Noble. ICML IMLH 2022

[Workshop] [Paper]  


Interpretable Deep Learning: More than just a pretty picture

SPAAM Seminar Series, Warwick, 2023

Reviewing Experience

Program committee for MICCAI Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC) 2023


Program committee for MICCAI Domain Adaptation and Representation Transfer (DART) 2022