This is the repository for the collection of Graph Neural Network for Traffic Forecasting.

This is the repository for the collection of Deep Learning for Traffic Prediction Problems.

Implementation of deep learning models for time series in PyTorch.

Some Conferences' accepted paper lists (including AI, ML, Robotic)

Paper list in traffic prediction field

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

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.

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

🕖 A curated list of awesome time series databases, benchmarks and papers

List of papers, code and experiments using deep learning for time series forecasting

Bayesian Deep Learning: A Survey

Spatio-temporal modeling 论文列表（主要是graph convolution相关)

Machine learning for transportation data imputation and prediction.

list of papers, code, and other resources

Time Series Analysis Models Source Code with Deep Learning Algorithms

Practical Time-Series Analysis, published by Packt

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

A comprehensive survey on the time series domains

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

An up-to-date list of time-series related papers in AI venues.

tfts: Time Series Deep Learning Models in TensorFlow

Time series forecasting with PyTorch

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…

A paper list for ST-based represenation learning and POI recommenation.

这个开源项目主要是对经典的时间序列预测算法论文进行复现，模型主要参考自GluonTS，框架主要参考自Informer