This is the folder for relevant resources, e.g., course, tutorial, thesis, and blog.

Course

• Graph Neural Networks (ESE680) by Alejandro Ribeiro, University of Pennsylvania Link bilibili_video

• Deep Learning (with PyTorch) Link Github_repository

Competition

• 2019 Transportation Forecasting Competition workshop @ Transportation Research Board (TRB) 98th Annual Meeting Github_repository

• Highway Tollgates Traffic Flow Prediction (KDD Cup 2017): Link

Tutorial

• Ward I R, Joyner J, Lickfold C, et al. A Practical Guide to Graph Neural Networks[J]. arXiv preprint arXiv:2010.05234, 2020. Link

• 图神经网络相关算法详述及实现 Github_link

• Deep Graph Learning: Foundations, Advances and Applications (Tutorial @ KDD 2020) Link

  • 微信公众号：腾讯高校合作 犀牛鸟硬核 | 一文了解图深度学习的进展与应用

• Graph Representation Learning and Applications (Tutorial @ ECML/PKDD '20) Link

• Graph Neural Networks: Models and Applications (Tutorial @ AAAI 2020) Link

• Graph Mining & Learning (@NeurIPS 2020) Link

• 微信公众号：相约机器人

  • 图深度学习入门教程 Link

• 微信公众号：Datawhale

  • GNN专栏-秦州 Link

Thesis

• Zhang Y. Graph deep learning models for network-based spatio-temporal data forecasting: from dense to sparse[D]. UCL (University College London), 2020. Link

• Tang X. Modeling Spatiotemporality for Multivariate Time Series in Urban Applications[J]. 2020. Link

Blog

• Traffic prediction with advanced Graph Neural Networks (by DeepMind with Google Maps) Link