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Graph Neural Networks utilization for Spatiotemporal graphs. These methods will be applied into the problem of forecasting traffic flow on PEMS-Bay, METR-LA and Seattle Loop Datasets

License: MIT License

Makefile 0.02% Python 2.52% Jupyter Notebook 97.45% Shell 0.01%
forecasting-algorithm graph-convolutional-networks graph-neural-networks spatio-temporal-data traffic-forecasting traffic-graphs

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gnn-spacetimegraphs's Issues

你好,作者。想请教您的代码中layers文件中关于几个注意力模块的问题。

 我想请问一下,您的gnn文件中layers.py文件中的几个注意力模块的代码,比如AGC,ASGCP这几个模块,是否可以嵌入到其他的交通流预测的神经网络模型中,我尝试了放进神经网络中,都是报错了。想请教您是否有尝试过类似操作,是否可行,希望能指点一下。非常感谢您在百忙之中阅读此消息,期待您的早日回信,万分感谢!

Some minor errors in the README file

  1. In the utils script commands, the last two commands may need to change their "output_dir".
command 2. After the "train a model" command, the config file path points directly to "configs/p3d.yml", but it should point to "configs/hypertuning/p3d.yml". 3. Before training, you may need to create two folders, "./saved_models" and "./studies/losses". Otherwise you may get the exception "Parent directory ./saved_models does not exist".

I'm learning about traffic flow forecasting. Your code has helped me a lot, thank you! 🌹

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