[{"title":"( 27 个子文件 51.94MB ) ASTGCN:基于注意力的时空图卷积网络进行流量预测(ASTGCN)AAAI 2019","children":[{"title":"ASTGCN-master","children":[{"title":".gitignore <span style='color:#111;'> 76B </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 49B </span>","children":null,"spread":false},{"title":"data","children":[{"title":"README.md <span style='color:#111;'> 111B </span>","children":null,"spread":false},{"title":"PEMS04","children":[{"title":"pems04.npz <span style='color:#111;'> 31.43MB </span>","children":null,"spread":false},{"title":"distance.csv <span style='color:#111;'> 4.74KB </span>","children":null,"spread":false}],"spread":true},{"title":"PEMS08","children":[{"title":"pems08.npz <span style='color:#111;'> 17.67MB </span>","children":null,"spread":false},{"title":"distance.csv <span style='color:#111;'> 3.94KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"model","children":[{"title":"model_config.py <span style='color:#111;'> 2.24KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"astgcn.py <span style='color:#111;'> 13.14KB </span>","children":null,"spread":false},{"title":"mstgcn.py <span style='color:#111;'> 7.98KB </span>","children":null,"spread":false}],"spread":true},{"title":"papers","children":[{"title":"ASTGCN_ppt.pdf <span style='color:#111;'> 2.28MB </span>","children":null,"spread":false},{"title":"2019 AAAI_Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting.pdf <span style='color:#111;'> 1.09MB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 4.16KB </span>","children":null,"spread":false},{"title":"lib","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 8.79KB </span>","children":null,"spread":false},{"title":"metrics.py <span style='color:#111;'> 1.11KB </span>","children":null,"spread":false},{"title":"data_preparation.py <span style='color:#111;'> 5.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"figures","children":[{"title":"model.png <span style='color:#111;'> 186.23KB </span>","children":null,"spread":false}],"spread":true},{"title":"configurations","children":[{"title":"PEMS04.conf <span style='color:#111;'> 430B </span>","children":null,"spread":false},{"title":"PEMS08.conf <span style='color:#111;'> 430B </span>","children":null,"spread":false}],"spread":true},{"title":"test","children":[{"title":"test_metrics.py <span style='color:#111;'> 760B </span>","children":null,"spread":false},{"title":"test_utils.py <span style='color:#111;'> 3.37KB </span>","children":null,"spread":false},{"title":"test_data_preperation.py <span style='color:#111;'> 552B </span>","children":null,"spread":false},{"title":"test_model.py <span style='color:#111;'> 2.23KB </span>","children":null,"spread":false}],"spread":true},{"title":"docker","children":[{"title":"Dockerfile <span style='color:#111;'> 190B </span>","children":null,"spread":false}],"spread":true},{"title":"train.py <span style='color:#111;'> 8.81KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]