1 citations · 1 across the 3 of their papers we have counts for
3 papers
nlin.CD2024
Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble
Marc Bocquet, Alban Farchi, Tobias S. Finn +5
We investigate the ability to discover data assimilation (DA) schemes meant for chaotic dynamics with deep learning. The focus is on learning the analysis step of sequential DA, fr…
physics.ao-ph2022
Towards hourly three-dimensional ensemble data assimilation of screen-level observations into coupled atmosphere-land models
Tobias Finn, Gernot Geppert, Felix Ament
We explore the potential of three-dimensional data assimilation for assimilating sparsely-distributed 2-metre temperature observations across the coupled atmosphere-land interface…
cs.LG2021★ 1 cited
Self-Attentive Ensemble Transformer: Representing Ensemble Interactions in Neural Networks for Earth System Models
Tobias Sebastian Finn
Ensemble data from Earth system models has to be calibrated and post-processed. I propose a novel member-by-member post-processing approach with neural networks. I bridge ideas fro…