139 citations · 139 across the 1 of their papers we have counts for
4 papers
Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning
Mike Walmsley, Lewis Smith, Chris Lintott +10
We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN…
Machine Learning for the Zwicky Transient Facility
Ashish Mahabal, Umaa Rebbapragada, Richard Walters +47
The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning…
Optimizing the Human-Machine Partnership with Zooniverse
Lucy Fortson, Darryl Wright, Chris Lintott +1
Over the past decade, Citizen Science has become a proven method of distributed data analysis, enabling research teams from diverse domains to solve problems involving large quanti…
Integrating human and machine intelligence in galaxy morphology classification tasks
Melanie R. Beck, Claudia Scarlata, Lucy F. Fortson +8
Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification metho…