Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces
cs.LG, physics.ao-ph
Submitted: 2026-09-24
Updated: 2026-09-24
Terminology
Sources
- Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation
- OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model
- MODS: Multi-source Observations Conditional Diffusion Model for Meteorological State Downscaling
- PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems
- LO-SDA: Latent Optimization for Score-based Atmospheric Data Assimilation
- WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling
- High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator
- WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models
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