GitHub

Simplifying Graph Convolutional Networks

This repo contains an example implementation of the Simple Graph Convolution (SGC) model, described in the ICML2019 paper Simplifying Graph Convolutional Networks. SGC removes the nonlinearities and ...
IEEE

Self-Attention Graph Convolution Residual Network for Traffic Data Completion

Abstract: Complete and accurate traffic data is critical in urban traffic management, planning and operation. In fact, real-world traffic data contains missing values due to multiple factors, such as ...
IEEE

Self-Attention Graph Convolution Imputation Network for Spatio-Temporal Traffic Data

Abstract: Missing data in time series is a pervasive problem that serves as obstacles for subsequent traffic data analysis. Consequently, extensive research works have been conducted on traffic ...
GitHub

kaize0409/Awesome-Graph-OOD

This repository for the paper 📘: A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. The README file here maintains a list of ...
www.cs.cmu.edu

Tom Mitchell

For example, AI applications to medical diagnosis should be regulated very differently from AI applications to self-driving cars. U.S. National Academies report on AI and the Future of Work, study ...