3 citations · 5 across the 8 of their papers we have counts for
3 papers · 1 filter
Building Understandable Messaging for Policy and Evidence Review (BUMPER) with AI
Katherine A. Rosenfeld, Maike Sonnewald, Sonia J. Jindal +2
We introduce a framework for the use of large language models (LLMs) in Building Understandable Messaging for Policy and Evidence Review (BUMPER). LLMs are proving capable of provi…
A Moonshot for AI Oracles in the Sciences
Bryan Kaiser, Tailin Wu, Maike Sonnewald +2
Nobel laureate Philip Anderson and Elihu Abrahams once stated that, "even if machines did contribute to normal science, we see no mechanism by which they could create a Kuhnian rev…
The Importance of Architecture Choice in Deep Learning for Climate Applications
Simon Dräger, Maike Sonnewald
Machine Learning has become a pervasive tool in climate science applications. However, current models fail to address nonstationarity induced by anthropogenic alterations in greenh…