graph neural networks

Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Knowledge graphs (KGs), as a structured form of knowledge representation, have been widely applied in the real world. Recently, …
PDF Code
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting
Recent studies focus on formulating the traffic forecasting as a spatio-temporal graph modeling problem. They typically construct a …
PDF
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs
Graph neural architecture search (NAS) has gained popularity in automatically designing powerful graph neural networks (GNNs) with …
PDF Code
Robust Graph Representation Learning for Local Corruption Recovery
The performance of graph representation learning is affected by the quality of graph input. While existing research usually pursues a …
PDF
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Unsupervised graph representation learning (UGRL) has drawn increasing research attention and achieved promising results in several …
PDF Code
Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs
Link prediction on dynamic graphs is an important task in graph mining. Existing approaches based on dynamic graph neural networks …
PDF Code Poster Slides
Neighbor Contrastive Learning on Learnable Graph Augmentation
Recent years, graph contrastive learning (GCL), which aims to learn representations from unlabeled graphs, has made great progress. …
PDF Code
Simple and Efficient Heterogeneous Graph Neural Network
Heterogeneous graph neural networks (HGNNs) deliver the powerful capability to embed rich structural and semantic information of a …
PDF Code
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
Most existing machine learning models are trained based on the closed-world assumption, where the test data is assumed to be drawn …
PDF Code
Contrastive Graph Similarity Networks
Graph similarity learning is a significant and fundamental issue in the theory and analysis of graphs, which has been applied in a …