no code implementations • 6 May 2024 • Tao Han, Zhenghao Chen, Song Guo, Wanghan Xu, Lei Bai
To mitigate this issue, we introduce an efficient neural codec, the Variational Autoencoder Transformer (VAEformer), for extreme compression of climate data to significantly reduce data storage cost, making AI-based meteorological research portable to researchers.
no code implementations • 28 Feb 2024 • Wanghan Xu, Bin Shi, Ao Liu, Jiqiang Zhang, Bo Dong
In recent years, with the rapid development of graph neural networks (GNN), more and more graph datasets have been published for GNN tasks.
no code implementations • 6 Feb 2024 • Junchao Gong, Lei Bai, Peng Ye, Wanghan Xu, Na Liu, Jianhua Dai, Xiaokang Yang, Wanli Ouyang
Precipitation nowcasting based on radar data plays a crucial role in extreme weather prediction and has broad implications for disaster management.
1 code implementation • 2 Feb 2024 • Wanghan Xu, Kang Chen, Tao Han, Hao Chen, Wanli Ouyang, Lei Bai
Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to traditional physics-based dynamical models.
no code implementations • 24 Jan 2024 • Wanghan Xu
However, whether the isomorphic discrimination power of k-WL is strictly increasing for more complex 3D graphs, or whether there exists k that can discriminate all 3D graphs, remains unexplored.