Session 7 - Machine Learning and Forecasting

Conveners: Véronique Delouille (ROB), Meng Jin (LMSAL)
Thursday 1/11, 09:00 - 10:30

Since its commissioning in 2010, SDO has captured one high resolution image every second. A large community effort resulted in the implementation of a series of algorithms for the autonomous detection and tracking of solar events, with outputs available within the Heliophysical Event Knowledgebase (HEK). Machine learning and deep learning have the ability to further leverage on these data, algorithms and database, and to tackle open complex problems. This session will discuss mathematical, statistical, computational, and machine learning techniques for information processing of SDO and solar data, with emphasis on: autonomous prediction of solar events from heterogenous data (magnetogram, EUV imagers, spectrometer), supervised and unsupervised detection, tracking of solar events and features at large and small scales, dimensionality reduction, image enhancement, methods for enriching and mining the HEK e.g. in view of spatio-temporal pattern discovery. Of special interest are techniques that allow for a progress towards reconciling theory with observations.

Plenary speaker: Vincent Barra (Université Clermont-Ferrand)




Talks

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Thursday November 1, 09:00 - 10:30
09:00Deep Learning and solar data processing - an introduction with applicationsBarra, VInvited Oral
09:30Sunspot Group Classification using Neural NetworksMaloney, SOral
09:45AI-generated magnetogram and EUV image of the Carrington event and the estimation of its Dst valueLee, HOral
10:00Solar EUV Spectral Irradiance by Deep LearningWright, POral
10:15Statistically Identifying Systematics from Far-side Acoustic ImagesHess webber, SOral

Posters

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e-Posters

Estimating solar far-side magnetic flux from STEREO EUV observations by deep learningChen, R

p-Posters

Supervised Neural Networks for Helioseismic Ring-diagram InversionsHanson, C
Extracting Solar Physics from 151 Million EUV ImagesKirk, M
Irradiance Coronal Dimming and its Connection to CME KineticsMason, J
Coronal holes detection using supervised classificationDelouille, V
Driving Scientific Discovery with Machine Learning and AI at the NASA GSFC Center for HelioAnalyticsThompson, B
SHARPs and SMARPs: 22 years of solar active region dataBobra, M
Photospheric Magnetic Field Properties of Flaring vs. Flare-quiet active regions, V: Results from HMILeka, K
A deep learning approach to forecast tomorrow's solar wind parameters.Shneider, C
AI-generated EUV images from SDO/HMI magnetograms by deep learningPark, E
Combining sparsity DEM inversions with event tracking for AIA dataBethge, C