We present the first version of the Automatic Learning for the Rapid Classification of Events
(ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient …

Classification is valuable and necessary in spectral analysis, especially for data-driven
mining. Along with the rapid development of spectral surveys, a variety of classification …

In astronomical surveys, such as the Zwicky Transient Facility, supernovae (SNe) are
relatively uncommon objects compared to other classes of variable events. Along with this …

The improvement of observation capabilities has expanded the scale of new data available
for time domain astronomy research, and the accumulation of observational data continues …

With the availability of large-scale surveys like Kepler and TESS, there is a pressing need for
automated methods to classify light curves according to known classes of variable stars. We …

The advent of wide-field sky surveys has led to the growth of transient and variable source
discoveries. The data deluge produced by these surveys has necessitated the use of …

The remarkable capacity of artificial intelligence (AI) to analyze enormous quantities of
information and create precise forecasts has led to its growing prominence in the field of …

Resampling is the most commonly used method for dealing with imbalanced data, in
addition to modifying the algorithm mechanism, it can, for example, generate new minority …

Dataset imbalances pose a significant challenge to predictive modeling in both medical and
financial domains, where conventional strategies, including resampling and algorithmic …

The optical and UV variability of the majority of active galactic nuclei may be related to the
reprocessing of rapidly changing X-ray emission from a more compact region near the …