S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales
physics.ao-ph, cs.AI, cs.LG
Submitted: 2026-10-02
Updated: 2026-10-02
Sources
- FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
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- Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
- V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
- Hierarchical Planning with Latent World Models
- LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
- Message Passing Neural PDE Solvers
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- XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change
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