AGU Fall Meeting Session: NG007 – Machine Learning in Space WeatherJuly 11, 2019, from Enrico Camporeale
We would like to draw your attention to the Session NG007 – Machine Learning in Space Weather.
Abstract submission deadline: July 31 (11:59 EDT)
In the last few years, several ground-breaking milestones were reached in Artificial Intelligence, such as image recognition at super-human accuracy and the notorious defeat of world champion Lee Sedol in the game of Go.
Advances in Machine Learning (ML) have been fueled by the growth of available data and ubiquity of capable computing technologies. Space physics and geophysics are characterized by impressive amounts of freely-available data and can certainly benefit from data-driven ML applications.
This session will focus on applications of Machine Learning to Space Weather problems across the subdisciplines of the Heliophysics and the physics of the Earth’s environment, involving as well the coupling of the interplanetary plasma with the upper atmosphere. Contributions ranging from black-box models to data-driven physics-based simulations are welcome, including (but not limited to) regression and classification problems, inverse problems, dimensionality reduction, automatic event identification, Bayesian inference, feature extraction, deep learning, and reinforcement learning.