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WeatherBench: A benchmark dataset for data-driven weather forecasting, , , , , and . (2020)cite arxiv:2002.00469Comment: Github repository: https://github.com/pangeo-data/WeatherBench; Data download: https://mediatum.ub.tum.de/1524895.Climate-Invariant Machine Learning., , , , , , , , , and 1 other author(s). CoRR, (2021)WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models., , and . CoRR, (2022)Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection., , , and . CoRR, (2019)Neural General Circulation Models., , , , , , , , , and 6 other author(s). CoRR, (2023)Deep learning to represent subgrid processes in climate models, , and . Proceedings of the National Academy of Sciences, 115 (39): 9684--9689 (2018)Increasing the accuracy and resolution of precipitation forecasts using deep generative models., and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 10555-10571. PMLR, (2022)Neural networks for post-processing ensemble weather forecasts., and . CoRR, (2018)Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling., , , and . CoRR, (2019)WeatherBench 2: A benchmark for the next generation of data-driven global weather models., , , , , , , , , and 8 other author(s). CoRR, (2023)