Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era. - Brian Nord; Andrew J. Connolly; Jamie Kinney; Jeremy Kubica; Gautaum Narayan; Joshua E. G. Peek; Chad Schafer; Erik J. Tollerud; Camille Avestruz; Gutti Jogesh Babu; Simon Birrer; Douglas Burke; et al. (CoRR, 2019)

Deep learning insights into cosmological structure formation. - Luisa Lucie-Smith; Hiranya V. Peiris; Andrew Pontzen; Brian Nord; Jeyan Thiyagalingam (CoRR, 2020)

Discovering the building blocks of dark matter halo density profiles with neural networks. - Luisa Lucie-Smith; Hiranya V. Peiris; Andrew Pontzen; Brian Nord; Jeyan Thiyagalingam; Davide Piras (CoRR, 2022)

Insights into the origin of halo mass profiles from machine learning. - Luisa Lucie-Smith; Susmita Adhikari; Risa H. Wechsler (CoRR, 2022)

Explaining dark matter halo density profiles with neural networks. - Luisa Lucie-Smith; Hiranya V. Peiris; Andrew Pontzen (CoRR, 2023)

A robust estimator of mutual information for deep learning interpretability. - Davide Piras; Hiranya V. Peiris; Andrew Pontzen; Luisa Lucie-Smith; Ningyuan Guo; Brian Nord (Mach. Learn. Sci. Technol., 2023)

ΛCDM and early dark energy in latent space: a data-driven parametrization of the CMB temperature power spectrum. - Davide Piras; Laura Herold; Luisa Lucie-Smith; Eiichiro Komatsu (CoRR, 2025)