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 ...
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 ...
GitHub

An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem

🚀 Update: If you are interested in this work, you may be interested in our latest paper and up-to-date codebase bringing together several architectures and learning paradigms for learning-driven TSP ...
IEEE

Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting

Abstract: Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due to the time-varying traffic patterns and the complicated spatial dependencies on road ...