在A Comprehensive Survey on Graph Neural Networkshttps://arxiv.org/pdf/1901.00596.pdf中提出了将图神经网络进一步地分为Recurrentgraph neural networks(RecGNNs)递归图神经网络、Convolutional graph neural networks (ConvGNNs)卷积图神经网络、Graph autoencoders (GAEs)图自动编码器和 Spatial-temporal graph neural...
目前基于GCN的自编码器的方法主要有:Graph Autoencoder (GAE)和Adversarially Regularized Graph Autoencoder (ARGA) 图自编码器的其它变体有: Network Representations with Adversarially Regularized Autoencoders (NetRA) Deep Neural Networks for Graph Representations (DNGR) Structural Deep Network Embedding (SDNE) ...
我们将首先回顾基于GCN的AutoEncoder,然后总结这一类别中的其他变体。 目前基于GCN的自编码器的方法主要有:Graph Autoencoder (GAE)和Adversarially Regularized Graph Autoencoder (ARGA) 图自编码器的其它变体有: Network Representations with Adversarially Regularized Autoencoders (NetRA) Deep Neural Networks for Gr...
我们将首先回顾基于GCN的AutoEncoder,然后总结这一类别中的其他变体。目前基于GCN的自编码器的方法主要有:Graph Autoencoder (GAE)和Adversarially Regularized Graph Autoencoder (ARGA)图自编码器的其它变体有:Network Representations with Adversarially Regularized Autoencoders (NetRA)Deep Neural Networks for Graph ...
To address the aforementioned issues, we propose the denoising autoencoder integrated with self-supervised learning (SSL) in graph neural networks (DAS-GNN). In DAS-GNN, the query extraction module based on denoising autoencoder can mine multiple user interests and assist long-term interest to ...
(1)提出了一种新的GNN分类方法,将GNN分为:recurrent GNN (RecGNN,循环GNN)、convolutional GNN(ConvGNN,卷积GNN)、graph autoencoder(GAE,图自编码器)和spatial-temporal GNN (STGNN,时空GNN)。 (2)全面的概述:对于每种类型的GNN,都对其中具有代表性的模型进行了详细的描述,并进行了必要的比较,总结了相应的算...
Examples include variational autoencoders (VAEs)134, generative adversarial networks (GANs)135, reinforcement learning136, recurrent neural networks (RNNs)137, and flow-based generative models138,139,140. Several architectures of VAEs have been developed to work with different types of input data, ...
Variational Graph Auto-Encoders Thomas N. Kipf, Max Welling arXiv 1611 Scalable Graph Embedding for Asymmetric Proximity Chang Zhou, Yuqiong Liu, Xiaofei Liu, Zhongyi Liu, Jun Gao AAAI 2017 Fast Network Embedding Enhancement via High Order Proximity Approximation ...
3.3 Graph Autoencoders 3.4 Spatial-Temporal Graph Neural Networks 4 GRAPH NEURAL NETWORKS PIPELINE 4.1 Graph Definition 4.2 Task Definition 4.3 Model Definition 5 PIPELINE APPLICATION TO EDA 5.1 Logic Synthesis 5.2 Verification and Signoff 5.3 Floorplanning ...
TrustAGI-Lab/Awesome-Graph-Neural-Networks Star2.2k Code Issues Pull requests Paper Lists for Graph Neural Networks deep-learningconvolutional-networksgraph-attentiongraph-networkgenerated-graphsgraph-auto-encoder UpdatedDec 29, 2023 VGraphRNN/VGRNN ...