no code implementations • 31 May 2024 • Christina Winkler, Paula Harder, David Rolnick
Predictions of global climate models typically operate on coarse spatial scales due to the large computational costs of climate simulations.
no code implementations • 12 Nov 2023 • Christina Winkler, David Rolnick
This study investigates how conditional normalizing flows can be applied to remote sensing data products in climate science for spatio-temporal prediction.
1 code implementation • 29 Nov 2019 • Christina Winkler, Daniel Worrall, Emiel Hoogeboom, Max Welling
Normalizing Flows (NFs) are able to model complicated distributions p(y) with strong inter-dimensional correlations and high multimodality by transforming a simple base density p(z) through an invertible neural network under the change of variables formula.