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AIFS model code isn't public, so not exactly sure how it is working, although its apparently similar to GraphCast. On a new update, it uses a reduced Gaussian octahedral grid for the processor, and the encoder an decoder use attention-based graph neural networks. The processor grid has 40320 grid points, which is processes as a sequence with a sliding attention window.
Context
It is another approach that might be worth including here. Good use for #76, as it could be another internal graph representation to easily slot in and try out.
Possible Implementation
The text was updated successfully, but these errors were encountered:
https://www.ecmwf.int/en/about/media-centre/aifs-blog/2024/first-update-aifs
Detailed Description
AIFS model code isn't public, so not exactly sure how it is working, although its apparently similar to GraphCast. On a new update, it uses a reduced Gaussian octahedral grid for the processor, and the encoder an decoder use attention-based graph neural networks. The processor grid has 40320 grid points, which is processes as a sequence with a sliding attention window.
Context
It is another approach that might be worth including here. Good use for #76, as it could be another internal graph representation to easily slot in and try out.
Possible Implementation
The text was updated successfully, but these errors were encountered: