GitHub

DeepDrawing: A Deep Learning Approach to Graph Drawing

This is the code repository for our IEEE VIS19 Paper entitled "DeepDrawing: A Deep Learning Approach to Graph Drawing". We propose a deep learning based approach to learn from existing graph drawings ...
GitHub

DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting

The model is composed by three main components: the generative model (VRNN) and two graph neural networks. The first graph network operates on agents' goals, expressed as specific areas of the ...
IEEE

Collaborative Decision-Reinforced Self-Supervision for Attributed Graph Clustering

Abstract: Attributed graph clustering aims to partition nodes of a graph structure into different groups. Recent works usually use variational graph autoencoder (VGAE) to make the node representations ...
IEEE

STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

Abstract: The success of intelligent transportation systems relies heavily on accurate traffic prediction, in which how to model the underlying spatial-temporal information from traffic data has come ...