M squared Weather: A Benchmark for Joint Multi-Station and Multi-Variable Weather Forecasting
cs.LG, stat.ML
Submitted: 2026-09-30
Updated: 2026-09-30
Code: https://github.com/hnu-vis/M2-Weather
Terminology
Sources
- Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
- Temporal Query Network for Efficient Multivariate Time Series Forecasting
- Timer: Generative Pre-trained Transformers Are Large Time Series Models
- xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
- StationPDE: Station-Oriented Surface PDE Learning for Multi-Station Multivariate Weather Forecasting
- Are Transformers Effective for Time Series Forecasting?
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks