Morris et al. Future Directions in Foundations of Graph Machine Learning. ICML 2024 Zhao et al. GraphAny: A Foundation Model for Node Classification on Any Graph. Arxiv 2024. Code on Github Dong et al. Universal Link Predicto...
Chapter 3: Graph Neural Networks Part II Foundations Chapter 4: Graph Neural Networks for Node Classification ··· (更多) 原文摘录 ··· 图神经网络(Graph Neural Network,GNN)是近年来在传统深层神经网络基础上发展起来的一个新领域,也可以称之为图上的深度学习。20世纪末,基于传统人工神经网络的深度学...
([3] C. Aggarwal and K. Subbian, ‘‘Evolutionary network analysis: A survey,’’ Comput. Surv., vol. 47, no. 1, p. 10, Jul. 2014. J. Zhang, ‘‘A survey on streaming algorithms for massive graphs,’’ in Managing and Mining Graph Data. Boston, MA, USA: Springer, 2010,pp. ...
In this chapter, we will systematically organize the existing research of GNNs along three axes: foundations, frontiers, and applications. We will introduce the fundamental aspects of GNNs ranging from the popular models and their expressive powers, to the scalability, interpretability and robustness ...
Theoretical foundations of graph neural networks. CST Wednesday Seminar, https://petar-v.com/talks/GNN-Wednesday.pdf (2021). Gilmer, J., Schoenholz, S. S., Riley, P. F., Vinyals, O. & Dahl, G. E. Neural message passing for quantum chemistry. Preprint at https://doi.org/10.48550/...
本篇文章主要概括了关于动态图最新研究(2020)的survey:Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey. 本文的目录如下: 1 Introduction 2 Dynamic Networks 2.1 Dynamic Network Representations 2.2 Link Duration Spectrum ...
Hands-On Graph Neural Networks Using Python begins with the fundamentals of graph theory and shows you how to create graph datasets from tabular data. As you advance, you’ll explore major graph neural network architectures and learn essential concepts such as graph convolution, self-attention, ...
Graph Neural Networks in Natural Language Processing. In Graph Neural Networks: Foundations, Frontiers, and Applications; Springer: Berlin/Heidelberg, Germany, 2022; pp. 463–481. [Google Scholar] Vashishth, S.; Yadati, N.; Talukdar, P. Graph-based deep learning in natural language processing....
Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey. arxiv 2020. paper Skarding, Joakim and Gabrys, Bogdan and Musial, Katarzyna. Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks. arxiv 2020. paper Zhiqian Chen, Fa...
Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey 本文首先给出了动态网络的定义和分类,然后分别从编码和解码的角度介绍了图神经网络模型如何用于动态图的嵌入表示以及完成链路预测任务 动态网络 定义 动态网络是随时间变化的复杂网络。链接和节点可能出现和消失。 一个 动态...