STCFormer: Adaptive Spatio-Temporal Modeling with Dynamic Cluster Transformer for Station-based Weather Forecasting

arXiv:2610.00377 · cs.LG, stat.ML · Submitted 2026-09-30 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/hnu-vis/STCFormer

Terminology

• Clustering — 43× in this paper · explained in 2 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Multivariate Time Series — 16× in this paper
• Ablation — 12× in this paper · explained in 1 episode
• Time Series Forecasting — 12× in this paper · explained in 3 episodes
• Cluster-Guided Attention Block — 7× in this paper
• Guided attention — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Aggregation — 4× in this paper · explained in 1 episode
• Foundation Model — 4× in this paper · explained in 3 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptivity — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Spectral clustering — 1× in this paper · explained in 2 episodes

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