Time-domain astrophysics continues to grow rapidly, with the inception of new surveys
drastically increasing data volumes. Democratized, distributed approaches to training sets …

This review summarizes popular unsupervised learning methods, and gives an overview of
their past, current, and future uses in astronomy. Unsupervised learning aims to organise the …

Star image registration is the most important step in the application of astronomical image
differencing, stacking, and mosaicking, which requires high robustness, accuracy, and real …

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys
drastically increasing data volumes. Democratised, distributed approaches to training sets …

In recent years, deep learning has achieved excellent performance in a growing number of
application fields. With the help of high computation and large-scale datasets, deep learning …