PROSWIN: Probabilistic Solar Wind Speed Forecasting Using Deep Distributional Regression From Solar Images
Paper recorded by Signals 4 on 2026-09-22 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23
Category: cs.LG · 机器学习 · first seen 2026-09-23
Abstract
Accurately predicting fast solar wind conditions is challenging, as uncertainties are large and unquantified by traditional single-value prediction models. In particular, the risks of high-speed solar wind streams (HSSs), which can cause damage to technological infrastructure, cannot be reliably assessed without probabilistic forecasts. We present PROSWIN, a probabilistic machine learning model th
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Cite this page: PROSWIN: Probabilistic Solar Wind Speed Forecasting Using Deep Distributional Regression From Solar Images: the #7 most recent of 263 cs.LG papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/proswin-probabilistic-solar-wind-speed-forecasting-using-deep-distributional-reg.html
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