Can semi-supervised learning reduce the amount of manual labelling required for effective radio galaxy morphology classification? - Inigo V. Slijepcevic; Anna M. M. Scaife (CoRR, 2021)

Radio Galaxy Zoo: Using semi-supervised learning to leverage large unlabelled data-sets for radio galaxy classification under data-set shift. - Inigo V. Slijepcevic; Anna M. M. Scaife; Mike Walmsley; Micah Bowles; Ivy Wong; Stanislav S. Shabala; Hongming Tang (CoRR, 2022)

Towards Galaxy Foundation Models with Hybrid Contrastive Learning. - Mike Walmsley; Inigo Val Slijepcevic; Micah Bowles; Anna M. M. Scaife (CoRR, 2022)

A New Task: Deriving Semantic Class Targets for the Physical Sciences. - Micah Bowles; Hongming Tang; Eleni Vardoulaki; Emma L. Alexander; Yan Luo; Lawrence Rudnick; Mike Walmsley; Fiona Porter; Anna M. M. Scaife; Inigo Val Slijepcevic; Gary Segal (CoRR, 2022)

Zoobot: Adaptable Deep Learning Models for Galaxy Morphology. - Mike Walmsley; Campbell Allen; Ben Aussel; Micah Bowles; Kasia Gregorowicz; Inigo Val Slijepcevic; Chris J. Lintott; Anna M. M. Scaife; Maja Jablonska; Kosio Karchev; Denise Lanzieri; Devina Mohan; et al. (J. Open Source Softw., 2023)

Scaling Laws for Galaxy Images. - Mike Walmsley; Micah Bowles; Anna M. M. Scaife; Jason Shingirai Makechemu; Alexander J. Gordon; Annette M. N. Ferguson; Robert G. Mann; James Pearson; Jürgen J. Popp; Jo Bovy; Joshua S. Speagle; Hugh Dickinson; et al. (CoRR, 2024)