Implementation of the paper: "Aurora: A Foundation Model of the Atmosphere" in PyTorch [](https://discord.gg/qUtxnK2NMf) # Aurora [](https://discord.gg/agora-999382051935506503) [](https://www.youtube.com/@kyegomez3242) [](https://www.linkedin.com/in/kye-g-38759a207/) [](https://x.com/kyegomezb)  Community and Open Source Implementation of the paper: "Aurora: A Foundation Model of the Atmosphere" in PyTorch: [Paper link](https://arxiv.org/abs/2405.13063) ## Install ```bash pip3 install aurora-torch ``` ## Example ```python import torch from aurora_torch.main import SwinTransformerUNet3D from loguru import logger # Test with random input tensor of shape (B, D, H, W, C) B, D, H, W, C = 2, 16, 64, 64, 32 model = SwinTransformerUNet3D(input_dim=C, output_dim=C) input_tensor = torch.rand(B, D, H, W, C) # Forward pass through the model output = model(input_tensor) logger.info(f"Output shape: {output.shape}") ``` # License MIT # Bibtex ```bibtex @misc{bodnar2024aurora, title={Aurora: A Foundation Model of the Atmosphere}, author={Cristian Bodnar and Wessel P. Bruinsma and Ana Lucic and Megan Stanley and Johannes Brandstetter and Patrick Garvan and Maik Riechert and Jonathan Weyn and Haiyu Dong and Anna Vaughan and Jayesh K. Gupta and Kit Tambiratnam and Alex Archibald and Elizabeth Heider and Max Welling and Richard E. Turner and Paris Perdikaris}, year={2024}, eprint={2405.13063}, archivePrefix={arXiv}, primaryClass={physics.ao-ph} } ``` # References - [Blog Release: Introducing Aurora: The first large-scale foundation model of the atmosphere](https://www.microsoft.com/en-us/research/blog/introducing-aurora-the-first-large-scale-foundation-model-of-the-atmosphere/) - [Paper Link](https://arxiv.org/abs/2405.13063) <!-- - [Microsoft Twitter Thread]() --> Source: https://github.com/KyeGomezB/Aurora