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Julia Kaltenborn

2 accepted papers

2025

Causal Climate Emulation with Bayesian Filtering

NeurIPS 2025poster

Traditional models of climate change use complex systems of coupled equations to simulate physical processes across the Earth system. These simulations are highly computationally expensive, limiting our predictions of climate change and analyses of its causes and effects. Machine learning has the po…

Cited by 0SourceScholar
2023

ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning

NeurIPS 2023poster

Climate models have been key for assessing the impact of climate change and simulating future climate scenarios. The machine learning (ML) community has taken an increased interest in supporting climate scientists’ efforts on various tasks such as climate model emulation, downscaling, and prediction…