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20112025
most citedHow to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events

75 citations · 188 across the 27 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

astro-ph.SR2021

Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods

Atharv Yeoleka, Sagar Patel, Shreejaa Talla +4

The Space-Weather ANalytics for Solar Flares (SWAN-SF) is a multivariate time series benchmark dataset recently created to serve the heliophysics community as a testbed for solar f…

cs.CV2021★ 1 cited

Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures

Azim Ahmadzadeh, Dustin J. Kempton, Yang Chen +1

General-purpose object-detection algorithms often dismiss the fine structure of detected objects. This can be traced back to how their proposed regions are evaluated. Our goal is t…

cs.LG2021★ 1 cited

Towards Synthetic Multivariate Time Series Generation for Flare Forecasting

Yang Chen, Dustin J. Kempton, Azim Ahmadzadeh +1

One of the limiting factors in training data-driven, rare-event prediction algorithms is the scarcity of the events of interest resulting in an extreme imbalance in the data. There…

cs.LG2021★ 27 cited

All-Clear Flare Prediction Using Interval-based Time Series Classifiers

Anli Ji, Berkay Aydin, Manolis K. Georgoulis +1

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 region…

astro-ph.SR2021★ 75 cited

How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events

Azim Ahmadzadeh, Berkay Aydin, Manolis K. Georgoulis +3

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. Taking f…