5 papers
Uncertainty-Aware Solar Flare Regression
Jinsu Hong, Chetraj Pandey, Berkay Aydin
Current solar flare predictions often lack precise quantification of their reliability, resulting in frequent false alarms, particularly when dealing with datasets skewed towards e…
Ordinal Encoding as a Regularizer in Binary Loss for Solar Flare Prediction
Chetraj Pandey, Jinsu Hong, Anli Ji +2
The prediction of solar flares is typically formulated as a binary classification task, distinguishing events as either Flare (FL) or No-Flare (NF) according to a specified thresho…
Surya: Foundation Model for Heliophysics
Sujit Roy, Johannes Schmude, Rohit Lal +30
Heliophysics is central to understanding and forecasting space weather events and solar activity. Despite decades of high-resolution observations from the Solar Dynamics Observator…
SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction
Sujit Roy, Dinesha V. Hegde, Johannes Schmude +22
This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory (SDO), specifically designed to advance machine…
Embedding Ordinality to Binary Loss Function for Improving Solar Flare Forecasting
Chetraj Pandey, Anli Ji, Jinsu Hong +2
In this paper, we propose a novel loss function aimed at optimizing the binary flare prediction problem by embedding the intrinsic ordinal flare characteristics into the binary cro…