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Found 5 papers, 2 papers with code
Explainable Deep Learning-based Solar Flare Prediction with post hoc Attention for Operational Forecasting
This paper presents a post hoc analysis of a deep learning-based full-disk solar flare prediction model.
Towards Coupling Full-disk and Active Region-based Flare Prediction for Operational Space Weather Forecasting
We utilized an equal weighted average ensemble of two base learners' flare probabilities as our baseline meta learner and improved the capabilities of our two base learners by training a logistic regression model.
All-Clear Flare Prediction Using Interval-based Time Series Classifiers
An all-clear flare prediction is a type of solar flare forecasting that puts more emphasis on predicting non-flaring instances (often relatively small flares and flare quiet regions) with high precision while still maintaining valuable predictive results.
How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events
We present a case study of solar flare forecasting by means of metadata feature time series, by treating it as a prominent class-imbalance and temporally coherent problem.
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data
This is in particular prevalent in interdisciplinary research where the theoretical aspects are sometimes overshadowed by the challenges of the application.
