2022年3月28日 · In this work, we propose TGL, a unified framework for large-scale offline Temporal Graph Neural Network training where users can compose various Temporal Graph …

This repo is the open-sourced code for our work TGL: A General Framework for Temporal Graph Training on Billion-Scale Graphs. Our temporal sampler is implemented using C++, please …

In this work, we propose TGL, a unified framework for large-scale ofline Temporal Graph Neural Network training where users can compose various Temporal Graph Neural Networks with …

In this work, we propose TGL, a unified framework for large-scale offline Temporal Graph Neural Network training where users can compose various Temporal Graph Neural Networks with …

2023年2月8日 · Temporal Graph Learning (TGL) has become a prevalent technique across diverse real-world applications, especially in domains where data can be represented as a …

2023年12月16日 · This workshop bridges the conversation among different areas such as temporal knowledge graph learning, graph anomaly detection, and graph representation …

2024年1月9日 · Temporal graphs serve as a valuable tool for modelling dynamic systems that undergo evolution over time. Concep-tually, temporal graphs can be likened to time series …

2024年1月8日 · Abstract: This document aims to familiarize readers with temporal graph learning (TGL) through a concept-first approach. We have systematically presented vital concepts …

In this work, we propose TGL, a unified framework for large-scale offline Temporal Graph Neural Network training where users can compose various Temporal Graph Neural Networks with …

This workshop bridges the conversation among different areas such as temporal knowledge graph learning, graph anomaly detection, and graph representation learning. It aims to share...