2024/08/21 · Through extensive experiments, our proposed method outperforms other specially designed baseline models on multiple surface variables. Notably, ...

Abstract—Accurately retrieving surface meteorological states at arbitrary locations is of great application significance in weather forecasting and climate ...

NASA/ADS · Deriving Accurate Surface Meteorological States at Arbitrary Locations via Observation-Guided Continuous Neural Field Modeling.

We introduce the DeepPhysiNet framework, incorporating physical laws into deep learning models for accurate and continuous weather system modeling.

In this paper, we extend meteorological downscaling to arbitrary scattered station scales, establish a brand new benchmark and dataset, and retrieve ...

Deriving Accurate Surface Meteorological States at Arbitrary Locations via Observation-Guided Continous Neural Field Modeling. Article. Jan 2024. Zili ...

2024/02/20 · This state observer relies on transformer-based cross-attention to enable evaluation at arbitrary spatio-temporal locations. In a nutshell: (a) ...

2024/09/11 · Moreover, the model easily handles arbitrary patterns of missing data by treating them as latent variables. A number of recent articles have ...

2024/01/17 · Our practical implementation involves recurrent GNNs and a spatio-temporal attention observer capable of interpolating the solution at arbitrary ...

This article introduces the concept of computational image formation (CIF). Compared to the standard inverse problems where the goal is to recover the latent ...