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AtmoDist: Self-supervised Representation Learning for Atmospheric Dynamics

, and . (August 2022)arXiv:2202.01897 physics.

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AtmoDist: Self-supervised representation learning for atmospheric dynamics, and . Environmental Data Science, (2023)Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core., , and . PASC, page 10:1-10:10. ACM, (2024)A Multi-Scale Deep Learning Framework for Projecting Weather Extremes, , , , and . (2022)Controlling and Sampling Visibility Information on the Image Plane.. EGSR (EI&I), page 1-9. Eurographics Association, (2017)Improved Projective Dynamics Global Using Snapshots-based Reduced Bases., , and . SIGGRAPH Posters, page 4:1-4:2. ACM, (2023)Data driven weather forecasts trained and initialised directly from observations., , , , , , , , , and 4 other author(s). CoRR, (2024)Deep neural networks for geometric multigrid methods., , , and . CoRR, (2021)AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning, , , , , and . (2023)cite arxiv:2308.13280.On Parallelizing the MRRR Algorithm for Data-Parallel Coprocessors., and . PPAM (1), volume 6067 of Lecture Notes in Computer Science, page 396-402. Springer, (2009)On the Effective Dimension of Light Transport., and . Comput. Graph. Forum, 29 (4): 1399-1403 (2010)