GatedGCN是一种用来处理带有edge feature常见的GNN conv方法,其计算过程和框图如图所示 公式 hil+1=Alhil+Σj∈Nie^ijl⊙Blhjl 其中: e^ijl=σ(eijl+1)÷(Σj∈Niσ(eijl+1)+ε) eijl+1=Dlhil+Elhjl+Cleijl 计算框图 DGL实现 DGL目前已经实现了GateGCN: import torch import torch.nn as nn ...
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:...
Graph Convolutional Network (GCN) is proposed to model multi-relational image and generate more informative image representations. Recently, the relations between medical images are utilized to identify diseases. This paper proposes a Gated GCN with Attention Convolutional Binary Neural Tree (GGAC) for ...
et al. R-GCN: a residual-gated recurrent unit convolution network model for anomaly detection in blockchain transactions. Multimed Tools Appl 83, 87527–87551 (2024). https://doi.org/10.1007/s11042-023-17942-x Download citation Received01 July 2023 Revised03 October 2023 Accepted17 December ...
Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting - EEHITer/STAG-GCN
R-GCN: aresidual-gated recurrent unit convolution network model for anomaly detection in blockchain transactions 来自 Springer 喜欢 0 阅读量: 2 作者:R Rajmohan,TA Kumar,SG Sandhya,YC Hu 摘要: The domain of deep learning has provided an exemplary paradigm for how Artificial Intelligence (AI) ...
S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecastingGraph convolutional networkTrafficGated Recurrent Units Neural Network