基于这一出发点,2009年,在[2]中提出了graph neural network(GNN)。简单来讲,GNN是一种可以将图或图中的节点映射为某种向量表示的神经网络。为了使GNN能够用于处理序列问题,本文又提出了Gated Graph Sequence Neural Network(GGS-NN)。此外,针对GNN的训练问题,本文也做了相应的改进。实验证明,本文所提出了GGS-NN...
之前的图网络学习算法系列中,我们已经总结了如传统的Deepwalk,以及以卷积图神经网络为基础的GCN,GAT和GraphSAGE方法。今天,我们来学习下Graph Neural Network中的另一大类型,利用门控信息来进行更新的Gated Graph Neural Network(GGNN)。 论文:Gated graph sequence neural networks 链接:https://arxiv.org/pdf/1511.054...
Graph neural network(GNN) has become more widely used in recommendation systems in recent years, because of their ability to naturally integrate node information and topology. However, most of the current recommendation methods based on graph structure only focus on a single recommendation domain (...
是一个神经网络时,鼓励在网络雅可比矩阵(network’s Jacobian)的1-范数上使用惩罚项。请参阅附录A中的一个示例,该示例给出了收缩图(contraction maps)在图中长范围传播信息时遇到困难的直觉。 4. 门控图神经网络(GATED GRAPH NEURAL NETWORKS) 我们现在描述门控图神经网络(Gated Graph Neural Networks ,GG-NNs),...
Sample Code for Gated Graph Neural Networks. Contribute to microsoft/gated-graph-neural-network-samples development by creating an account on GitHub.
neural network models that has favorable inductive biases relative to purely sequence-based models (e.g., LSTMs) when the problem is graph-structured. We demonstrate the capabilities on some simple AI (bAbI) and graph algorithm learning tasks. We then show it achieves state-of-the-art ...
Github地址:https://github.com/Microsoft/gated-graph-neural-network-samples Gated Graph Neural Networks 六个基本公式: 基本公式 Equation (1):初始化步骤。它将节点注释(node annotations)复制到隐藏状态的第一个部分中,并用零填充其余部分。 Equation (2):用于在不同node之间传递信息。
Sample Code for Gated Graph Neural Networks. Contribute to microsoft/gated-graph-neural-network-samples development by creating an account on GitHub.
"Gated graph sequence neural networks". In: arXiv preprint arXiv:1511.05493 (2015).Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel. Gated graph sequence neural networks. arXiv preprint arXiv:1511.05493, 2015.Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel, "Gated graph ...
Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering笔记 来源: COLING 2018 Long Paper 原文 Movation 以往的模型在复杂问题(问题实体和答案实体之间相隔较远)上的表现很差。 作者认为: We claim that one needs to explicitly model the semantic structure to be able to ...