https://github.com/kyegomez/aurora

Implementation of the paper: "Aurora: A Foundation Model of the Atmosphere" in PyTorch
https://github.com/kyegomez/aurora

agents ai ml multi-agent weather weather-prediction

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Implementation of the paper: "Aurora: A Foundation Model of the Atmosphere" in PyTorch

• Host: GitHub
• URL: https://github.com/kyegomez/aurora
• Owner: kyegomez
• License: mit
• Created: 2024-06-04T15:29:00.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-10-07T20:33:13.000Z (4 months ago)
• Last Synced: 2024-10-10T20:19:46.984Z (4 months ago)
• Topics: agents, ai, ml, multi-agent, weather, weather-prediction
• Language: Python
• Homepage:
• Size: 2.98 MB
• Stars: 12
• Watchers: 4
• Forks: 2
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE

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README

        
[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Aurora

[![Join our Discord](https://img.shields.io/badge/Discord-Join%20our%20server-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/agora-999382051935506503) [![Subscribe on YouTube](https://img.shields.io/badge/YouTube-Subscribe-red?style=for-the-badge&logo=youtube&logoColor=white)](https://www.youtube.com/@kyegomez3242) [![Connect on LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/kye-g-38759a207/) [![Follow on X.com](https://img.shields.io/badge/X.com-Follow-1DA1F2?style=for-the-badge&logo=x&logoColor=white)](https://x.com/kyegomezb)

![Aurora](aurora.png)

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)