DeepClimateExtreme

We aim to develop a deep latent variable model framework to discover physically meaningful hidden structures from high-dimensional, spatiotemporal climate extreme data.

Meet the team

This project brings together a unique team of scientists with expertise in machine learning, causal inference, Bayesian statistics and climate science. It would lead to efficient and robust scientific ML methods that are flexible, scalable, physically meaningful, and also produce uncertainty estimates for high-dimensional spatiotemporal data. For climate science, this project will uncover hidden structures from climate extremes, significantly deepen our understanding and increase our capability to predict climate extremes and similar types of data across many scientific fields.