Machine Learning for Earth and Climate Sciences

Goal: Model and understand the Earth system with Machine Learning and Process Understanding

• Spatio-temporal anomaly and extreme events detection, anticipation and attribution
• Data-driven dynamic modelling and forecasting
• Hybrid modeling: linking physics and machine learning models
• Causal inference, Learning and explaining feature representations
• Earth and Climate model emulation, generative modelling and data-model fusion
• Benchmark synthetic and real datasets