A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.
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Updated
Dec 23, 2025 - Python
A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Code for our SIGKDD'22 paper Pre-training-Enhanced Spatial-Temporal Graph Neural Network For Multivariate Time Series Forecasting.
Traffic Graph Convolutional Recurrent Neural Network
Some TrafficFlowForecasting Solutions(交通流量预测解决方案)
[TKDD 2023] Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
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.
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
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"
[ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
STGM: Spatio-Temporal Graph Mixformer for Traffic Forecasting
[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting
[SIGKDD'2025] Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective
[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.
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