U-Cast (Rose-STL-Lab, ICML 2026)
github.com/rose-stl-lab/u-castSurprisingly simple and efficient frontier probabilistic weather forecaster built on a standard U-Net trained with deterministic MAE pre-training followed by short CRPS fine-tuning via Monte Carlo Dropout, matching or exceeding the probabilistic skill of GenCast and IFS ENS at 1.5° resolution with >10× less training compute than leading CRPS models and >10× lower inference latency than diffusion models; trains in under 12 H200 GPU-days and generates a 15-day ensemble forecast in 3 seconds, with official code and pretrained checkpoints (UCLA, 41+ stars, Apache 2.0)
Sourced from
- Awesome AI for Science — github.com/rose-stl-lab/u-cast
- GitHub — github.com/rose-stl-lab/u-cast
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