117 citations · 251 across the 6 of their papers we have counts for
6 papers
Six Maxims of Statistical Acumen for Astronomical Data Analysis
Hyungsuk Tak, Yang Chen, Vinay L. Kashyap +4
The production of complex astronomical data is accelerating, especially with newer telescopes producing ever more large-scale surveys. The increased quantity, complexity, and varie…
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting
Daniel Iong, Matthew McAnear, Yuezhou Qu +3
Gaussian Processes (GP) have become popular machine-learning methods for kernel-based learning on datasets with complicated covariance structures. In this paper, we present a novel…
Incorporating Polar Field Data for Improved Solar Flare Prediction
Mehmet Aktukmak, Zeyu Sun, Monica Bobra +4
In this paper, we consider incorporating data associated with the sun's north and south polar field strengths to improve solar flare prediction performance using machine learning m…
Predicting solar flares with machine learning: investigating solar cycle dependence
Xiantong Wang, Yang Chen, Gabor Toth +7
A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 ho…
Solar Flare Intensity Prediction with Machine Learning Models
Zhenbang Jiao, Hu Sun, Xiantong Wang +4
We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 024, 630, 1236 and 24$…
Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters
Yang Chen, Ward B. Manchester, Alfred O. Hero +7
We present several methods towards construction of precursors, which show great promise towards early predictions, of solar flare events in this paper. A data pre-processing pipeli…