- Deep Learning on Graphs: A Survey
- Graph Neural Networks: A Review of Methods and Applications
- Learning with Local and Global Consistency
- Ranking on Data Manifolds
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- Semi-supervised Classification with Graph Convolutional Networks
- Semantic Object Parsing with Graph LSTM
- Interpretable Structure-Evolving LSTM