mlsanityData to 14 Oct 2026

Machine learning in solar physics

arXiv 2306.15308 ↗First posted 27 Jun 2023astro-ph.SR astro-ph.IM cs.CVcited by 10

Not on the map. Why?

Abstract (arXiv)

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 using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 47 of its 305 references that are in the map. First posted on arXiv 27 Jun 2023.

Builds on

47 of 305 references.

References · 47

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  4. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  5. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  6. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  7. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  8. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 7,005
  9. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,733
  10. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  11. 2013Auto-Encoding Variational Bayescited by 4,053
  12. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
35 more
  1. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  2. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  3. 2016WaveNet: A Generative Model for Raw Audiocited by 1,722
  4. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,552
  5. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,436
  6. 2018On the Spectral Bias of Neural Networkscited by 1,341
  7. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,179
  8. 2015Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)cited by 1,070
  9. 2014NICE: Non-linear Independent Components Estimationcited by 1,058
  10. 2014Deep Learning in Neural Networks: An Overviewcited by 770
  11. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 533
  12. 2020On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networkscited by 284
  13. 2020Implicit Gradient Regularizationcited by 146
  14. 2019RVOS: End-to-End Recurrent Network for Video Object Segmentationcited by 88
  15. 2019A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Missioncited by 26
  16. 2019Predicting Solar Flares Using a Long Short-Term Memory Networkcited by 25
  17. 2020Photonic tensor cores for machine learningcited by 16
  18. 2017Enhancing SDO/HMI images using deep learningcited by 11
  19. 2017A hybrid supervised/unsupervised machine learning approach to solar flare predictioncited by 11
  20. 2019Stokes Inversion based on Convolutional Neural Networkscited by 9
  21. 2020Identifying and Tracking Solar Magnetic Flux Elements with Deep Learningcited by 9
  22. 2019Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar Physicscited by 8
  23. 2019Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Coronacited by 6
  24. 2022Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translationcited by 6
  25. 2021Fast and Accurate Emulation of the SDO/HMI Stokes Inversion with Uncertainty Quantificationcited by 5
  26. 2022A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Datacited by 5
  27. 2021Machine learning initialization to accelerate Stokes profile inversionscited by 4
  28. 2021SCSS-Net: Solar Corona Structures Segmentation by Deep Learningcited by 4
  29. 2019Solar image denoising with convolutional neural networkscited by 3
  30. 2021SynthIA: A Synthetic Inversion Approximation for the Stokes Vector Fusing SDO and Hinode into a Virtual Observatorycited by 3
  31. 2021Accelerating non-LTE synthesis and inversions with graph networkscited by 2
  32. 2022Towards on-sky adaptive optics control using reinforcement learningcited by 2
  33. 2017DeepVel: deep learning for the estimation of horizontal velocities at the solar surfacecited by 1
  34. 2022Using Multiple Instance Learning for Explainable Solar Flare Predictioncited by 1
  35. 2022Large-Scale Spatial Cross-Calibration of Hinode/SOT-SP and SDO/HMIcited by 1

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 4; 2025: 5.

10 papers.

  1. 2025Surya: Foundation Model for Heliophysicscited by 6
  2. 2025Predicting partially observable dynamical systems via diffusion models with a multiscale inference schemecited by 5
  3. 2023Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Modelscited by 4
  4. 2025SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Predictioncited by 4
  5. 2024AI Foundation Model for Heliophysics: Applications, Design, and Implementationcited by 3
  6. 2024Deep Computer Vision for Solar Physics Big Data: Opportunities and Challengescited by 2
  7. 2025Physics-informed Attention-enhanced Fourier Neural Operator for Solar Magnetic Field Extrapolationscited by 1
  8. 2024Machine learning for reconstruction of polarity inversion lines from solar filamentscited by 0
  9. 2024Transfer Learning for Deep Learning-based Prediction of Lattice Thermal Conductivitycited by 0
  10. 2025Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognitioncited by 0