Machine Learning for Earth and Climate Sciences


Fellows & Scholars

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