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View Code? Open in Web Editor NEWThis is an official Pytorch implementation of Conditional Local Convolution for Spatio-temporal Meteorological Forecasting, AAAI 2022
This is an official Pytorch implementation of Conditional Local Convolution for Spatio-temporal Meteorological Forecasting, AAAI 2022
根据您的代码复现出来,在Humidity数据集上的结果和论文中的结果差了一个数量级,您在论文中写的结果是MAE:0.4531,复现出来的结果是MAE:4.531左右。而且根据您在arxiv上的Figure3(c)中,也很明显的显示出MAE的横坐标是从1.0-5.0,那最终结果反而是0.4531。
Congratulations for your AAAI 2022 work, i have met some bug when i run your code. There is something wrong in the dataset folder that your dataset lack of 'lonlat' part. Wish your regard, Thank you!
Hi, thanks for your excellent work!
When I checked the raw WeatherBench data, I found there were many vertical levels; but your AAAI paper just stated the "temperature, cloud cover, humidity and surface wind component". So whether is the temperature '2m_temperature'? The wind is '10m_u_component_of_wind' and '10m_v_component_of_wind'? And how about the humidity? Is it 'Specific_humidity' or 'Relative_humidity'? Which level does it belong to?
Looking forward to your reply, thanks!
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