LibCity: An Open Library for Urban Spatial-temporal Data Mining

A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.

Traffic Graph Convolutional Recurrent Neural Network

Code for our SIGKDD'22 paper Pre-training-Enhanced Spatial-Temporal Graph Neural Network For Multivariate Time Series Forecasting.

Some TrafficFlowForecasting Solutions(交通流量预测解决方案)

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).

This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.

Paper list in traffic prediction field

Code for our CIKM'22 paper Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting.

Code for our VLDB'22 paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

Useful resources for traffic prediction, including popular papers, datasets, tutorials, toolkits, and other helpful repositories.

[AAAI23] This it the official github for AAAI23 paper "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting"

STGM: Spatio-Temporal Graph Mixformer for Traffic Forecasting

[ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks

[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting

[CIKM 2023] This is the official source code of "TrendGCN: Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting" based on Pytorch.

[CIKM 2022] Source codes of CIKM2022 Full Paper "Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities"

[IJCNN 2021] Unified Spatio-Temporal modeling for traffic forecasting using Graph Convolutional Network