Nature

Few shot learning for Korean winter temperature forecasts

To address the challenge of limited training samples, this study employs the model-agnostic meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to predict winter ...
Nature

Unsupervised deep learning framework for temperature-compensated damage assessment using ultrasonic guided waves on edge device

Fueled by the rapid development of machine learning (ML) and greater access to cloud computing and graphics processing units, various deep learning based models have been proposed for improving ...
Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...
Phys.org

Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at temperatures as high as ...