IEEE

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...
GitHub

This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].

Abstract: Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled data via a graph. As one of the most popular ...
GitHub

Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

This is the official code release of the following paper: Zixuan Li, Xiaolong Jin, Wei Li, Saiping Guan, Jiafeng Guo, Huawei Shen, Yuanzhuo Wang and Xueqi Cheng. Temporal Knowledge Graph Reasoning ...
IEEE

Graph Neural Network for Air Quality Prediction: A Case Study in Madrid

Abstract: Air quality monitoring, modelling and forecasting are considered pressing and challenging topics for citizens and decision-makers, including the government. The tools used to achieve the ...