Benefits of Saying I Don't Know When Analyzing and Modeling the Climate System With ML - Elizabeth Barnes

Explore the benefits of acknowledging uncertainty in climate system analysis and modeling using machine learning in this conference talk from the Machine Learning for Climate KITP conference. Delve into state-dependent predictability, challenges in regression problems, and controlled abstention networks. Gain insights into how big data and machine learning algorithms can advance climate science, enabling detailed analysis and potential causal inferences. Discover how this interdisciplinary approach can address complex climate questions and inform future predictions at regional and local scales.

Introduction
State dependent predictability
Challenges
Regression problems
Controlled abstention networks
Statedependent predictability
Questions
Discussion