activity
20192026
most citedMachine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations

9 citations · 25 across the 10 of their papers we have counts for

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14 papers · 1 filter

astro-ph.SR2026

Prediction of Magnetic Flux Evolution During Solar Active Region Emergence using Long Short-Term Memory Networks

Eren Dogan, Spiridon Kasapis, Sarang Patil +5

Solar active regions (ARs) are the primary drivers of space weather events, making their early prediction crucial for operational forecasting systems. We develop machine learning m…

astro-ph.SR2026

SolARED: Solar Active Region Emergence Dataset for Machine Learning Aided Predictions

Spiridon Kasapis, Eren Dogan, Irina N. Kitiashvili +6

The development of accurate forecasts of solar eruptive activity has become increasingly important for preventing potential impacts on space technologies and exploration. Therefore…

astro-ph.SR2026

Forecasting Continuum Intensity for Solar Active Region Emergence Prediction using Transformers

Jonas Tirona, Sarang Patil, Spiridon Kasapis +5

Early and accurate prediction of solar active region (AR) emergence is crucial for space weather forecasting. Building on established Long Short-Term Memory (LSTM) based approaches…

astro-ph.SR2025

Time-Dependence of Subsurface Solar Convection Using the Time-Distance Deep-Focus Method

John T. Stefan, Alexander G. Kosovichev, Gustavo Guerrero +1

We re-examine the deep-focus methodology of time-distance helioseismology previously used to estimate the power spectrum of the solar convection at a depth of about 30 Mm, which wa…

astro-ph.SR2024

Solar Active Regions Emergence Prediction Using Long Short-Term Memory Networks

Spiridon Kasapis, Irina N. Kitiashvili, Alexander G. Kosovichev +1

We developed Long Short-Term Memory (LSTM) models to predict the formation of active regions (ARs) on the solar surface. Using the Doppler shift velocity, the continuum intensity,…

astro-ph.SR2024★ 6 cited

Predicting the Emergence of Solar Active Regions Using Machine Learning

Spiridon Kasapis, Irina N. Kitiashvili, Alexander G. Kosovichev +2

To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic f…