Solar Flare Prediction
9 papers with code • 0 benchmarks • 0 datasets
Solar flare prediction in heliophysics
Benchmarks
These leaderboards are used to track progress in Solar Flare Prediction
Most implemented papers
Predicting Solar Flares Using a Long Short-Term Memory Network
JasonTLWang/LSTM-flare-prediction
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The essence of our approach is to model data samples in an AR as time series and use LSTMs to capture temporal information of the data samples.
DeepSun: Machine-Learning-as-a-Service for Solar Flare Prediction
Solar flare prediction plays an important role in understanding and forecasting space weather.
Using Multiple Instance Learning for Explainable Solar Flare Prediction
chuwyler/irismil
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In this work we leverage a weakly-labeled dataset of spectral data from NASAs IRIS satellite for the prediction of solar flares using the Multiple Instance Learning (MIL) paradigm.
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.
Shapelet-Based Counterfactual Explanations for Multivariate Time Series
In this work, we take advantage of the inherent interpretability of shapelets to develop a model agnostic multivariate time series (MTS) counterfactual explanation algorithm.
Explaining Full-disk Deep Learning Model for Solar Flare Prediction using Attribution Methods
This paper contributes to the growing body of research on deep learning methods for solar flare prediction, primarily focusing on highly overlooked near-limb flares and utilizing the attribution methods to provide a post hoc qualitative explanation of the model's predictions.
Explainable Deep Learning-based Solar Flare Prediction with post hoc Attention for Operational Forecasting
gsudmlab/explainingfulldisk
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This paper presents a post hoc analysis of a deep learning-based full-disk solar flare prediction model.
Exploring Deep Learning for Full-disk Solar Flare Prediction with Empirical Insights from Guided Grad-CAM Explanations
This study progresses solar flare prediction research by presenting a full-disk deep-learning model to forecast $\geq$M-class solar flares and evaluating its efficacy on both central (within $\pm$70$^\circ$) and near-limb (beyond $\pm$70$^\circ$) events, showcasing qualitative assessment of post hoc explanations for the model's predictions, and providing empirical findings from human-centered quantitative assessments of these explanations.
Towards Interpretable Solar Flare Prediction with Attention-based Deep Neural Networks
gsudmlab/fulldiskattention
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In this work, we developed an attention-based deep learning model as an improvement over the standard convolutional neural network (CNN) pipeline to perform full-disk binary flare predictions for the occurrence of $\geq$M1. 0-class flares within the next 24 hours.
