Colin J. Burke

Deblending and classifying astronomical sources with Mask R-CNN deep learning

Colin J. Burke, P. Aleo, Yu-Ching Chen et al. · Monthly Notices of the Royal Astronomical Society · 2019 · 90 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +19

Optical variability of quasars with 20-yr photometric light curves

Zachary Stone, Yue Shen, Colin J. Burke et al. · Monthly Notices of the Royal Astronomical Society · 2022 · 64 citations · Full text

Photometry, Sdss Stripe 82, Engineering +13

Dwarf AGNs from Optical Variability for the Origins of Seeds (DAVOS): insights from the dark energy survey deep fields

Colin J. Burke, Xin Liu, Yue Shen et al. · Monthly Notices of the Royal Astronomical Society · 2022 · 34 citations · Full text

High-redshift Extreme Variability Quasars from Sloan Digital Sky Survey Multiepoch Spectroscopy

Hengxiao Guo, Jiacheng Peng, Kaiwen Zhang et al. · The Astrophysical Journal · 2020 · 31 citations · Full text

Detection, instance segmentation, and classification for astronomical surveys with deep learning (<scp>deepdisc</scp>): <scp>detectron2</scp> implementation and demonstration with Hyper Suprime-Cam data

Grant Merz, Yichen Liu, Colin J. Burke et al. · Monthly Notices of the Royal Astronomical Society · 2023 · 27 citations

Convolutional Neural Network, Engineering, Machine Learning +17