Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …

Solar flares originate from the release of the energy stored in the magnetic field of solar
active regions, the triggering mechanism for these flares, however, remains unknown. For …

We introduce and make openly accessible a comprehensive, multivariate time series
(MVTS) dataset extracted from solar photospheric vector magnetograms in Spaceweather …

We developed a solar flare prediction model using a deep neural network (DNN) named
Deep Flare Net (DeFN). This model can calculate the probability of flares occurring in the …

We present a long short-term memory (LSTM) network for predicting whether an active
region (AR) would produce a ϒ-class flare within the next 24 hr. We consider three ϒ …

A probability forecast or probabilistic classifier is reliable or calibrated if the predicted
probabilities are matched by ex post observed frequencies, as examined visually in …

Solar flares are highly energetic events in the Sun's corona that affect Earth's space weather.
The mechanism that drives the onset of solar flares is unknown, hampering efforts to forecast …

We developed a flare prediction model using machine learning, which is optimized to predict
the maximum class of flares occurring in the following 24 hr. Machine learning is used to …

Coronal mass ejections (CMEs) were discovered in the early 1970s when space-borne
coronagraphs revealed that eruptions of plasma are ejected from the Sun. Today, it is known …