29 citations · 29 across the 11 of their papers we have counts for
5 papers · 1 filter
Reconstruction of Solar EUV Irradiance Using CaII K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification
Haodi Jiang, Qin Li, Jason T. L. Wang +2
Solar extreme ultraviolet (EUV) irradiance plays a crucial role in heating the Earth's ionosphere, thermosphere, and mesosphere, affecting atmospheric dynamics over varying time sc…
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model
Jialiang Li, Vasyl Yurchyshyn, Jason T. L. Wang +6
We present a novel deep generative model, named GenMDI, to improve the temporal resolution of line-of-sight (LOS) magnetograms of solar active regions (ARs) collected by the Michel…
Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model
Hongyang Zhang, Ju Jing, Jason T. L. Wang +6
We present a transformer model, named DeepHalo, to predict the occurrence of halo coronal mass ejections (CMEs). Our model takes as input an active region (AR) and a profile, where…
An Interpretable Machine Learning Approach to Understanding the Relationships between Solar Flares and Source Active Regions
Huseyin Cavus, Jason T. L. Wang, Teja P. S. Singampalli +4
Solar flares are defined as outbursts on the surface of the Sun. They occur when energy accumulated in magnetic fields enclosing solar active regions (ARs) is abruptly expelled. So…
Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning
Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang +6
The application of machine learning to the study of coronal mass ejections (CMEs) and their impacts on Earth has seen significant growth recently. Understanding and forecasting CME…