Graph-based Deep Learning Literature

The repository contains links to

• Conference Publications and the top 10 most-cited publications
• Related workshops
• Surveys / Literature Reviews / Books

in graph-based deep learning. The links to conference publications are arranged in the reverse chronological order of conference dates from the conferences below. Alternatively, please click on a year below beside a conference name to see publications of the conference in that year.

• Machine Learning Conferences

  • NeurIPS - 2020 | 2019 | 2018 | 2017 | 2016 | 2015

  • ICML - 2020 | 2019 | 2018 | 2017 | 2016

  • ICLR - 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2014

• Computer Vision Conferences

  • CVPR - 2020 | 2019 | 2018 | 2017

  • ICCV - 2019 | 2017

  • ECCV - 2020 | 2018

• Data Conferences

  • KDD - 2020 | 2019 | 2018

  • WebConf - 2021 | 2020 | 2019 | 2018

  • ICDM - 2020 | 2019 | 2018

• Artificial Intelligence Conferences

  • AAAI - 2021 | 2020 | 2019 | 2018 | 2017

  • IJCAI - 2020 | 2019 | 2018 | 2017

  • UAI - 2020 | 2019 | 2018

• Natural Language Processing Conferences

  • ACL - 2020 | 2019 | 2018

  • EMNLP - 2020 | 2019 | 2018 | 2017

  • NAACL - 2019 | 2018

Top 10 Most-cited Publications

1. Semi-Supervised Classification with Graph Convolutional Networks

2. Graph Attention Networks

3. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

4. Inductive Representation Learning on Large Graphs

5. Spectral Networks and Locally Connected Networks on Graphs

6. The Graph Neural Network Model

7. Neural Message Passing for Quantum Chemistry

8. Convolutional Networks on Graphs for Learning Molecular Fingerprints

9. Gated Graph Sequence Neural Networks

10. Learning Convolutional Neural Networks for Graphs

Related Workshops

• 2021

  • Geometrical and Topological Representation Learning (ICLR)

  • Graph Learning Benchmarks (WWW)

  • Deep Learning on Graphs: Methods and Applications (AAAI)

  • Graphs and more Complex structures for Learning and Reasoning (AAAI)

• 2020

  • Differential Geometry meets Deep Learning (NeurIPS)

  • Deep Learning on Graphs: Methods and Applications (KDD)

  • Mining and Learning with Graphs (KDD)

  • Graph Representation Learning and Beyond (GRL+) (ICML)

  • Bridge Between Perception and Reasoning: Graph Neural Networks and Beyond (ICML)

  • Deep Learning for Graphs (WWW)

  • Deep Learning on Graphs: Methodologies and Applications (AAAI)

• 2019

  • Graph Representation Learning (NeurIPS)

  • Scene Graph Representation and Learning (ICCV)

  • Deep Learning on Graphs: Methods and Applications (KDD)

  • Learning and Reasoning with Graph-Structured Representations (ICML)

  • Representation Learning on Graphs and Manifolds (ICLR)

• 2018

  • Relational Representation Learning (NeurIPS)