Train deep learning models for solar flare prediction and image-to-image translation.
npx skills add https://github.com/tykimos/ssw-plugin --skill ssw-plugin-ssw-ml
Please help me install this Agent Skill. Skill: ssw-plugin:ssw-ml Source: https://github.com/tykimos/ssw-plugin/tree/main/skills/ssw-ml Command: npx skills add https://github.com/tykimos/ssw-plugin --skill ssw-plugin-ssw-ml
This Skill enables the application of machine learning techniques to solar physics data, facilitating tasks like solar flare prediction and instrument translation.
Use the ssw-ml skill to train a U-Net model for image-to-image translation between STEREO and SDO instruments using preprocessed data.
High-intent search queries and answers about installing and using this skill.
Solar flare prediction involves training deep learning models like CNN+LSTM on historical solar activity data. This Skill enables you to train models on preprocessed solar observations to forecast flares and evaluate performance using standard metrics.
You can create PyTorch dataloaders for FITS files containing solar physics data. This Skill supports building dataloaders for preprocessed FITS files and paired multi-wavelength observations for both PyTorch and TensorFlow frameworks.
Performing image-to-image translation between solar instruments like STEREO and SDO is best handled using a U-Net architecture. This Skill allows you to train U-Net models on preprocessed solar EUV images to translate observations between different instruments.
This machine learning skill supports both PyTorch and TensorFlow for solar data analysis. You can create dataloaders in either framework to handle preprocessed FITS files and train deep learning models for solar physics tasks.
Model performance for predicting solar flares is evaluated using standard metrics. After training deep learning models on preprocessed solar observation data, the Skill calculates standard metrics to assess prediction accuracy and model effectiveness.
tykimosDownload solar observation data from SDO, STEREO, and Solar Orbiter missions.
paxlabs-incLog machine learning experiment metrics and artifacts to Weights & Biases.
tykimosVisualize solar EUV imagery, preprocessing results, and ML outputs with Python.
galeepRun machine learning algorithms for time series analysis with the aeon package.
