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

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

GMAN: A Graph Multi-Attention Network for Traffic Prediction (GMAN, https://fanxlxmu.github.io/publication/aaai2020/) was accepted by AAAI-2020.

Traffic Graph Convolutional Recurrent Neural Network

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

Summary of open source code for deep learning models in the field of traffic prediction

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.

This repo includes introduction, code and dataset of our paper Deep Sequence Learning with Auxiliary Information for Traffic Prediction (KDD 2018).

Paper list in traffic prediction field

[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.

Traffic data processing tools in LibCity

A collection of research on spatio-temporal data mining

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

HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival

Paper & Code & Dataset Collection of Spatial-Temporal Data Mining.

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

Predict traffic flow with LSTM. For experimental purposes only, unsupported!

Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data

[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"

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