Gated Graph ConvNets:我们利用VCNN的架构,Eq.(7),边缘控制机制,Eq.(8),得到以下模型: h^{l+1}_i = f_{G-GCNN}( h^l_i , \{h^l_j : j → i\} )= ReLU(U^lh^l_i + ∑_{j→i}\eta _{ij}\odot V^lh^l_i )……(Eq.11) Residual Gated Graph ConvNets:此外,我们利用的残差...
import torch import torch.nn as nn import torch.nn.functional as F import dgl.function as fn from dgl.nn import Gated """ GatedGCN: Residual Gated Graph ConvNets https://arxiv.org/pdf/1711.07553v2.pdf """ class GatedGCNLayer(nn.Module): """ Param: [] """ def __init__(self, ...
It includes models for Gated Graph Neural Networks (GGNN) and Residual Gated Graph ConvNets (RGGC). This was originally forked from JamesChuanggg/ggnn.pytorch and modified to include the RGGC model here. Both models are tested against the bAbi tasks dataset. Here's an example of bAbI ...
The code 01_residual_gated_graph_convnets_subgraph_matching.ipynb presents an application of the residual gated graph convNets for the problem of sub-graph matching. The code 02_residual_gated_graph_convnets_semisupervised_clustering.ipynb shows another application for the problem of semi-supervised...
原文:Modeling Relational Data with Graph Convolutional Networks 使用 R-GCN 恢复知识库,包含节点分类和连接预测两个任务。节点分类直接使用R-GCN训练节点的表示进入softmax;连接预测是一个autoencoder,R-GCN产生节点的潜在表示,张量分解模型DistMult探索学习到的节点表达,预测边。 1.亮点 1.建模多类型连... ...
Traditional methods use sensors deployed on roads to construct the spatial structure of the road network and capture spatial information by graph convolution. However, they ignore that the spatial correlation between nodes is dynamically changing, and using a fixed adjacency matrix cannot reflect the ...
Explainable predictive business process monitoring using gated graph neural networks J. Decis. Syst. (2020), pp. 1-16 forthcoming Google Scholar [65] N. Mehdiyev, P. Fettke Explainable artificial intelligence for process mining: A general overview and application of a novel local explanation approa...
Eng. (2021) 34:53 Page 6 of 16 Input Input Convlutional Layer 1 Max-Pooling Layer BN Layer 1 Convlutional Layer 1 Activation function Convolutional Layer 2 BN Layer 2 BN Layer 1 Activation function Convolutional Layer 2 Activation function Max-Pooling Layer BN Layer 2 Output Activation ...
importtorchimporttorch.nnasnnimporttorch.nn.functionalasFimportdgl.functionasfn"""GatedGCN: Residual Gated Graph ConvNetsAn Experimental Study of Neural Networks for Variable Graphs (Xavier Bresson and Thomas Laurent)https://arxiv.org/pdf/1711.07553v2.pdf"""classGatedGCNLayer(nn.Module):"""Param...
Chinese Named Entity Recognition Based on Gated Graph Neural Network Most Chinese Named Entity Recognition (CNER) models based on deep learning are implemented based on long short-term memory networks (LSTM) and conditional random fields (CRF). The serialized structure of LSTM is easily affected by...