Probabilistic Downscaling of Climate Variables Using Denoising Diffusion Probabilistic Models
Simplified, reproducible reimplementation of DeepMind's GraphCast weather model using graph neural networks (JAX · Haiku · Jraph). Runs on a single GPU, with honest negative-results reporting and detailed failure-mode analysis of a heavily scaled-down forecasting model.
Joint-embedding atmospheric world-model research for transferable, uncertainty-aware weather representation learning.
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