The Program

Day 1

22nd September

1 Contributed presentation

• Towards Transformer-based Homogenization of Satellite Imagery for Landsat-8 and Sentinel-2

Speaker : Venkatesh Thirugnana Sambandham

Keynote 2 : Almost 5 years of deep learning in Earth system modelling -- where do we come from and where do we go?

Speaker : Peter Düben

1 Contributed presentation

• Transformers show high skill in forecasting atmospheric ozone pollution in Europe

Speaker : Sebastian Hickman

2 Contributed presentations

• Forest classification with Transformers

Speaker : Matej Racic

• Domain transfer experiments with attention based architectures for satellite image time series based crop type classification

Speaker : Samuel Barrett

Day 2

23rd September

3 Contributed presentations

• Application of transformers to Satellite Image Time Series (SITS) land cover mapping for 1987-2020 in south-eastern Australia

Speaker : Tony Boston

• Towards Spatio-temporal Event Detection Using Transformer Models

Speaker : Diallo Diaoule

• Atmorep: Representation Learning for Spatio-Temporal Data in the Earth Sciences

Speaker : Christian Lessig

2 Contributed presentations

• The Self-Attentive Ensemble Transformer: Representing Ensemble Interactions in Neural Networks for Earth System Models

Speaker : Tobias Finn

• Multiscale Neural Operator: Learning Fast and Grid-independent PDE Solvers

Speaker : Bjoern Luetjens

Keynote 5 : Transforming weather forecasting using deep learning: Some of the remaining challenges

Speaker : Pedram Hassanzadeh