Predicting unobserved climate time series data at distant areas via spatial correlation using reservoir computing

arXiv:2406.03061 · cs.LG, nlin.CD, physics.ao-ph, stat.ML · Submitted 2024-06-05 · Read on arXiv

cs.LG, nlin.CD, physics.ao-ph, stat.ML

Submitted: 2024-06-05

Updated: 2024-06-05

Code: https://github.com/ToyotaCRDL/climate_data

Terminology

• Accuracy — 9× in this paper · explained in 1 episode
• Echo State Network — 8× in this paper
• Activation Function — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Leakly Integrator — 2× in this paper
• Cooperation — 1× in this paper · explained in 2 episodes
• Cross-ministerial Strategic Innovation Promotion Program — 1× in this paper
• Leakly Integrator Echo State Network — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
• Machine learning prediction of the MJO extends beyond one month

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