My essential reading list on GNNs

Give it a start if it helps you. Thank you :)

Content

1. Courses

2. Models

2.1 Basic Models

3. Applications

3.13 Intelligent Transport Network

Courses

1. Notes of CS224W: Machine Learning with Graphs CS224W. link

2. CS224W: Machine Learning with Graphs CS224W. link

Basic Models

1. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. NIPS 2016. paper

2. Graph Attention Networks. ICLR 2018. paper

   Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, Yoshua Bengio.

3. How Powerful are Graph Neural Networks? ICLR 2019. paper

   Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka.

4. Understanding Attention and Generalization in Graph Neural Networks. NeurIPS 2019. paper

   Boris Knyazev, Graham W. Taylor, Mohamed R. Amer.

Transportation

1. Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction. AAAI 2020. paper

   Weijia Zhang, Hao Liu, Yanchi Liu, Jingbo Zhou, Hui Xiong.

2. Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks. NeurIPS 2019. paper

   Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian Reid, Hamid Rezatofighi, Silvio Savarese.

3. GMAN: A Graph Multi-Attention Network for Traffic Prediction. AAAI 2020. paper

   Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi.