[Workshop] Transformers for Environmental Science
Attention-based neural networks are having a profound impact on areas such as natural language processing and computer vision. Their application to the Earth sciences is still in its infancy but has similar potential, for example, because of the complex nonlocal spatio-temporal interactions in this domain. In this workshop, we want to bring researchers from machine learning (ML) and Earth science together to discuss how transformers and related neural networks can lead to progress in applications such as weather and climate projections, vegetation analysis, remote sensing, downscaling (super resolution), and air pollution predictions. We also want to explore the challenges these applications pose to attention-based ML models, for example, what are appropriate embeddings of the data, what are suitable attention mechanisms and sparsity patterns, and how to represent many interacting physical fields in such architectures.
The workshop will take place in an informal setting on 22nd - 23rdSeptember at Lukasklause conference center in Magdeburg, Germany. Abstracts for presentations at the workshop can be submitted until 31st July 2022.