一、引言随着深度学习的发展,图神经网络(Graph Neural Network,简称GNN)已经成为处理图结构数据的强大工具。PyTorch和PyG是两个广泛使用的深度学习框架,可以方便地实现GNN模型。本文将介绍如何使用PyTorch和PyG实现图神经网络的经典模型,包括Graph Convolutional Network(GCN)、Graph Attention Network(GAT)和GraphSAGE。二、G...
PGExplainer:来自“Parameterized Explainer for Graph Neural Network (https://arxiv.org/abs/2011.04573) ”论文的 PGExplainer 模型。 AttentionExplainer:使用基于注意力的 GNN(例如 GATConv、GATv2Conv 或 TransformerConv)产生的注意力系数作为边解释的解释器 CaptumExplainer:基于 Captum (https://captum.ai/) 的...
Module): """Simple PyTorch Implementation of the Graph Attention Layer.""" def __init__(self): super(GATLayer, self).__init__() def forward(self, input, adj): print("") 线性变换 (Linear Transformation) 对于单个节点的节点特征我们有: \bar{h'}_i = \textbf{W} ⋅ \bar{h_i} ...
PGExplainer:来自“Parameterized Explainer for Graph Neural Network (https://arxiv.org/abs/2011.04573) ”论文的 PGExplainer 模型。 AttentionExplainer:使用基于注意力的 GNN(例如 GATConv、GATv2Conv 或 TransformerConv)产生的注意力系数作为边解释的解释器 CaptumExplainer:基于 Captum (https://captum.ai/) 的...
Graph Attention Network, ICLR2018 GAT(Graph Attention Network)(简写GAN已经被生成对抗网络占了...) Geometric deep learning on graphs and manifolds using mixture model CNNs (2016) MoNet: A general framework for spatial methods 2019 IJCAI graph convolution networks using heat kernal for Semi-supervised...
SuperGATfrom Kim and Oh:How To Find Your Friendly Neighborhood: Graph Attention Design With Self-Supervision(ICLR 2021) [Example] HGTConvfrom Huet al.:Heterogeneous Graph Transformer(WWW 2020) [Example] HEATConvfrom Moet al.:Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Traject...
graph pytorch networkx graph-visualization graph-convolutional-networks gcn cora pyg graph-attention-networks node-classification graph-neural-networks node-embedding gat pytorch-geometric gnn gatv2 Updated Apr 20, 2024 Jupyter Notebook arashsm79 / brain-opto-fmri-decoding-gnn Star 1 Code Issues ...
SuperGATfrom Kim and Oh:How To Find Your Friendly Neighborhood: Graph Attention Design With Self-Supervision(ICLR 2021) [Example] HGTConvfrom Huet al.:Heterogeneous Graph Transformer(WWW 2020) [Example] HEATConvfrom Moet al.:Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Traject...
Heterogeneous Graph Attention Network (HAN HGAT) 根据专家经验设置多条matapath(路径):点、边、点、边、点… 针对不同的matapath,节点i针对路径拿到其所有邻居节点j。 1.点和点计算attention并求和。使用多头注意力机制。 2.所有关系要聚合时算一个attention,其中q,w,b共享。
: Heterogeneous Graph Transformer (https://github.com/pyg-team/pytorch_geometric/blob/master/examples/hetero/hgt_dblp.pyxamples/hetero/hgt_dblp.py)] HEATConv from Mo et al.: Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction (CoRR 2021) SSGConv from Zhu et...