activity
20202022
most citedAttention-gating for improved radio galaxy classification

42 citations · 76 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.GA20221 cited

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 +4

In this work we examine the classification accuracy and robustness of a state-of-the-art semi-supervised learning (SSL) algorithm applied to the morphological classification of rad…

astro-ph.CO202217 cited

Quantifying Uncertainty in Deep Learning Approaches to Radio Galaxy Classification

Devina Mohan, Anna M. M. Scaife, Fiona Porter +2

In this work we use variational inference to quantify the degree of uncertainty in deep learning model predictions of radio galaxy classification. We show that the level of model p…

astro-ph.IM202115 cited

Structured Variational Inference for Simulating Populations of Radio Galaxies

David J. Bastien, Anna M. M. Scaife, Hongming Tang +2

We present a model for generating postage stamp images of synthetic Fanaroff-Riley Class I and Class II radio galaxies suitable for use in simulations of future radio surveys such…

astro-ph.GA202142 cited

Attention-gating for improved radio galaxy classification

Micah Bowles, Anna M. M. Scaife, Fiona Porter +2

In this work we introduce attention as a state of the art mechanism for classification of radio galaxies using convolutional neural networks. We present an attention-based model th…

astro-ph.GA20201 cited

Interactions among intermediate redshift galaxies. The case of SDSSJ134420.86+663717.8

Persis Misquitta, Micah Bowles, Andreas Eckart +4

We present the properties of the central supermassive black holes and the host galaxies of the interacting object SDSSJ134420.86+663717.8. We obtained optical long slit spectroscop…