Diffusion Convolutional Neural Network (DCNN) 扩散卷积神经网络 扩散卷积神经网络将图卷积视为扩散过程。它假设信息以一定的转移概率从一个节点转移到其相邻节点之一,使得信息分布在几轮后达到平衡。 DCNN 将扩散图卷积定义为: \mathbf{H}^{(k)}=f\left(\mathbf{W}^{(k)} \odot \mathbf{P}^{k} \mathbf...
Graph Wavelet Neural Network Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng ICLR 2019 Supervised Community Detection with Line Graph Neural Networks Zhengdao Chen, Xiang Li, Joan Bruna ICLR 2019 Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera, ...
Graph neural network, as a research hotspot in the field of recommendation system, can effectively deal with complex data structures. Although the existing recommendation model has made some progress, it still has obvious limitations. On the one hand, limited information about users and items may ...
2.3 Graph Attention Model (GAM) 图形注意力模型(GAM)提供了一个循环神经网络模型,以解决图形分类问题,通过自适应地访问一个重要节点的序列来处理图的信息。GAM模型被定义为 其中 是一个LSTM网络,fs是一个step network,它会优先访问当前节点 优先级高的邻居并将它们的信息进行聚合。 除了在聚集特征信息时将注意力...
Neural Network for Graphs: A Contextual Constructive Approach:空域图卷积早期代表作品 Diffusion-Convolutional Neural Networks:空域 Learning Convolutional Neural Networks for Graphs:空域 GNN和Network Embedding的比较# 什么是Network Embedding: 网络嵌入的目的是将网络节点表示为低维向量表示,既保留网络拓扑结构又保留...
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang WSDM 2018 Learning Structural Node Embeddings via Diffusion Wavelets Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec ...
3.2 DCNN(Diffusion-Convolution Neural Network) 每一层的更新方式:如第一层,更新某个节点首先找到与它距离为1的节点(也就是邻居节点),然后用原始的输入相加取平均值再乘以权重。第二层,更新更新某个节点首先找到与它距离为2的节点(这样也包括了它自自己本身).然后用原始的输入相加取平均值再乘以权重。
通用 图生成 MolGAN 《 Molgan: An implicit generative model for small molecular graphs》 决策优化 旅行商问题 GNN 《Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP》《Attention solves your tsp》 https://github.com/machine-reasoning-ufrgs/TSP-GNN https://github.co...
Graph Neural Networks: A Review of Methods and Applications A Comprehensive Survey on Graph Neural Networks 主题:图神经网络(Graph neural networks)综述 整合作者:Reddoge 1 引言 近年来,人工智能领域在科研领域取得了巨大的成功,影响到了人们生活的方方面面,其中,深度学习(Deep learning),作为机器学习的一分子...
Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Diffusion Model for Social Recommendation. Accepted by SIGIR2019.pdf. Le Wu, Junwei Li, Peijie Sun, Richang Hong, Yong Ge, and Meng Wang. DiffNet++: A Neural Influence and Interest Diffusion Netwo...