Traffic Prediction On Ne Bj

12 steps MAE

Results

Performance results of various models on this benchmark

		Paper Title
AGCRN	4.99	Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Graph WaveNet	4.99	Graph WaveNet for Deep Spatial-Temporal Graph Modeling
MTGNN	4.90	Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
GMAN	4.80	GMAN: A Graph Multi-Attention Network for Traffic Prediction
DGCRN	4.79	Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
RGDAN	4.68	RGDAN: A random graph diffusion attention network for traffic prediction

0 of 6 row(s) selected.