FarSky: Task-Aware Latent-Space Coupling for Generative Intra-Hour Solar Forecasting

arXiv:2608.11254 · cs.LG, physics.ao-ph, stat.AP · Submitted 2026-08-06 · Read on arXiv

Yann Fabel, Bijan Nouri, Milon Miah, Niklas Blum, Luis F. Zarzalejo, Julia Kowalski, Robert Pitz-Paal

cs.LG, physics.ao-ph, stat.AP

Submitted: 2026-08-06

Updated: 2026-08-13

Code: https://github.com/yuhao-nie/SkyGPT

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Latent Representation — 35× in this paper · explained in 2 episodes
• Latent Representations — 22× in this paper · explained in 3 episodes
• Benchmark — 18× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Calibration — 13× in this paper · explained in 9 episodes
• Probabilistic Forecasting — 11× in this paper · explained in 3 episodes
• Diffusion Model — 10× in this paper · explained in 10 episodes
• Representation Learning — 9× in this paper · explained in 3 episodes
• Scaled Persistence — 9× in this paper
• F1 Score — 8× in this paper · explained in 4 episodes
• Generative Model — 7× in this paper · explained in 2 episodes
• Latent Space — 7× in this paper · explained in 7 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Decoder — 6× in this paper · explained in 2 episodes
• Diffusion Models — 5× in this paper · explained in 9 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Generative Models — 4× in this paper · explained in 3 episodes
• Domain Shift — 3× in this paper · explained in 7 episodes
• Latent Diffusion Model — 3× in this paper · explained in 3 episodes
• Performance Gap — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 6 episodes
• Systematic Bias — 3× in this paper · explained in 3 episodes
• Weight Decay — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 4 episodes
• Evaluation Protocol — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Hyperparameters — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Training Objective — 2× in this paper · explained in 3 episodes
• Continuous Ranked Probability Score (CRPS) — 1× in this paper · explained in 2 episodes
• Convolutional Neural Network (CNN) — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• False Negatives — 1× in this paper · explained in 2 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Global Horizontal Irradiance — 1× in this paper
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 16 episodes
• Transformer Model — 1× in this paper · explained in 2 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 9 episodes

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