paper
2022
Extremes & hazards
New model or method
Graph neural network6 h–3 days Journal
2022-05-18
012
May 2022
Tong Zhang, Jie Liu, Jianlong Wang
Geocarto International
Graph convolutional network with learned spatio-temporal affinities and a class-imbalance loss predicts rare rainstorms better than competing methods on two datasets.
Rainstorm prediction via a deep spatio-temporal-attributed affinity network
In one sentence. Graph convolutional network with learned spatio-temporal affinities and a class-imbalance loss predicts rare rainstorms better than competing methods on two datasets.
Labels
- Topic
- Extremes & hazards
- Type
- New model or method
- Method
- Graph neural network
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1080/10106049.2022.2076914 OpenAlex:W4280599789
- Added
- 2026-10-22
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