90 citations · 164 across the 4 of their papers we have counts for
7 papers
Lessons Learned from the Two Largest Galaxy Morphological Classification Catalogues built by Convolutional Neural Networks
Ting-Yun Cheng, H. Domínguez Sánchez, J. Vega-Ferrero +54
We compare the two largest galaxy morphology catalogues, which separate early and late type galaxies at intermediate redshift. The two catalogues were built by applying supervised…
Harvesting the Lyα forest with convolutional neural networks
Ting-Yun Cheng, Ryan Cooke, Gwen Rudie
We develop a machine learning based algorithm using a convolutional neural network (CNN) to identify low HI column density Ly absorption systems ($\log{N_{\mathrm{HI}}}/{\rm cm}…
Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks
Ting-Yun Cheng, Christopher J. Conselice, Alfonso Aragón-Salamanca +57
We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3…
Beyond the Hubble Sequence -- Exploring Galaxy Morphology with Unsupervised Machine Learning
Ting-Yun Cheng, Marc Huertas-Company, Christopher J. Conselice +3
We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantised variational autoencoder (VQ-VAE) and hiera…
Galaxy Merger Rates up to z 3 using a Bayesian Deep Learning Model A Major-Merger classifier using IllustrisTNG Simulation data
Leonardo Ferreira, Christopher J. Conselice, Kenneth Duncan +3
Merging is potentially the dominate process in galaxy formation, yet there is still debate about its history over cosmic time. To address this we classify major mergers and measure…
Identifying Strong Lenses with Unsupervised Machine Learning using Convolutional Autoencoder
Ting-Yun Cheng, Nan Li, Christopher J. Conselice +3
In this paper we develop a new unsupervised machine learning technique comprised of a feature extractor, a convolutional autoencoder (CAE), and a clustering algorithm consisting of…