[图表示学习] 2 动态图 (Dynamic Graph)最新研究总结（2020）
网页这篇文章主要的工作有：（1）介绍了dynamic network的基本框架和分类；（2）总结了现有的动态网络模型；（3）介绍了DGNN (Dynamic Graph Neural Network)；（4）告诉我们DGNN如何去做预测
从几篇综述区分Dynamic Graph和Spatial-temporal Graph - CSDN …
网页2021年2月28日 · 动态图神经网络（Dynamic Graph Neural Networks）通常是GNN和RNN相结合的形式，用GNN处理网络，用RNN处理时序信息。 动态图神经网络 伪动态模型. 模型的动态属性不适合动态数据. 离散动态图神经网络
What are Dynamic Graphs and Why They are Interesting?
网页2021年9月4日 · We define a dynamic graph in a similar manner but as a series of snapshots, i.e, G = (G₁, G₂, …., Gₜ) where Gₜ = (Vₜ, Eₜ) and T is the number of snapshots. In dynamic graphs, new nodes can form and create links with existing nodes, or nodes can disappear, thus terminating the existing links.
Dynamic/Temporal Graph动态图|时态图相关论文，数据集汇总
网页1. Representation Learning for Dynamic Graphs: A Survey. 作者： Seyed Mehran Kazemi, et al. (Borealis AI) 发表时间： 2020.3. 发表于： JMLR 21 (2020) 1-73. 标签： 动态图表示，综述. 概述： 针对目前动态图表示已有的方法，从encoder/decoder的角度进行了概述，覆盖面很全，是了解动态图研究的必读工作。 链接： https:// deepai.org/publication/ relational-representation-learning-for-dynamic-knowledge-graphs-a-survey. 2.
Dynamic Graph Representation Learning with Neural Networks: A …
网页2023年4月12日 · Dynamic Graph Representation Learning with Neural Networks: A Survey. Leshanshui Yang, Sébastien Adam, Clément Chatelain. In recent years, Dynamic Graph (DG) representations have been increasingly used for modeling dynamic systems due to their ability to integrate both topological and temporal information in a …
[2404.18211] A survey of dynamic graph neural networks - arXiv.org
网页2024年4月28日 · This paper provides a comprehensive review of the fundamental concepts, key techniques, and state-of-the-art dynamic GNN models. We present the mainstream dynamic GNN models in detail and categorize models based on how temporal information is incorporated. We also discuss large-scale dynamic GNNs and pre-training techniques.
Dynamic Graph Algorithms: What We Know and What We Don’t
网页2023年11月15日 · A dynamic graph algorithm is a data structure that maintains information about a graph while it is modified through local operations such as edge or vertex insertions or deletions. These data structures can be used in real-world applications such as maintaining clusters in large social networks or …
Title: Deep learning for dynamic graphs: models and benchmarks
网页2023年7月12日 · With the aim of fostering research in the domain of dynamic graphs, at first, we survey recent advantages in learning both temporal and spatial information, providing a comprehensive overview of the current state-of-the-art in the domain of representation learning for dynamic graphs.
Recent Advances in Fully Dynamic Graph Algorithms – A Quick …
网页2022年12月13日 · We propose a new data structure for manipulating graphs, called h-graph, which is particularly suited for designing dynamic algorithms. The structure itself is simple, consisting basically of a triple of elements, for each vertex of the graph.
网页recent advances in representation learning for dynamic graphs, including dynamic knowledge graphs. We describe existing models from an encoder-decoder perspective, categorize these encoders and decoders based on the techniques they employ, and analyze the approaches in each category.