Empirical Research over the possible advantages of pretraining a Graph Neural Network for Classification by using Link Prediction. We used GCN, GAT and GraphSAGE with minibatch generation. Done for the Learning From Networks course taught by professor Fabio Vandin at the University of Padova ...
GNNs-for-Link-Prediction Some GNNs are implemented using PyG for link prediction tasks, including: GCN, GraphSAGE, GAT, Node2Vec、RGCN、HGT and HAN, which will continue to be updated in the future. Dependencies numpy==1.22.4 pandas==1.3.3 scikit-learn==1.2.1 torch==1.12.1+cu113 torch-...
2 基础案例 前置知识:GCN_基于图卷积网络的半监督学习 2.1 节点嵌入可视化 数据集:Zachary 空手道俱乐部网络 描述了空手道俱乐部 34 名成员的社交网络,包含成员间的互动链接 最终目的是线性分离社区并正确分类大多数节点,同时进行可视化 环境准备与绘图辅助函数定义 importosimporttorch%matplotlibinlineimportnetworkxasnximpo...
import torch from torch import Tensor from torch_geometric.nn import GCNConv from torch_geometric.datasets import Planetoid dataset = Planetoid(root='.', name='Cora') class GCN(torch.nn.Module): def __init__(self, in_channels, hidden_channels, out_channels): super().__init__() self.co...
Added a link-predictionexampleofnn.conv.RGCNConv(thanks to @moritzblum) Added anexampleofnn.pool.MemPooling(thanks to @wsad1) Added areturn_attention_weightsargument fornn.conv.TransformerConv(thanks to @wsad1) Batch support forutils.homophily(thanks to @wsad1) ...
请注意,edge_index中的元素必须只包含范围为{ 0, ..., num_nodes - 1}的索引。(这意味着当索引的范围过大,但是这些值并不连续,如{ 1, 22, 357}时,需要对索引进行重新编码)因为我们希望最终的数据表示尽可能紧凑,例如,我们希望通过x[0]和x[1]分别索引第一条边(0, 1)的源节点和目的节点特征。可以通...
In the first glimpse of PyG, we implement the training of a GNN for classifying papers in a citation graph. For this, we load theCoradataset, and create a simple 2-layer GCN model using the pre-definedGCNConv: importtorchfromtorchimportTensorfromtorch_geometric.nnimportGCNConvfromtorch_geometr...
nn import GCN import torch_geometric.transforms as T from torch_geometric.datasets import Planetoid transform = T.ToSparseTensor(layout=torch.sparse_csr) dataset = Planetoid("Planetoid", name="Cora", transform=transform) model = GCN(in_channels, hidden_channels, num_layers=2) model = model(...
SEALlink prediction example (thanks to @muhanzhang) ClusterGCNConv Cluster-GCN PPIexample (thanks to @CFF-Dream) WeightedEdgeSamplerfor GraphSAINT (thanks to @KiddoZhu) Betternum_workerssupport forGraphSAINT The automatic addition of self-loops can now be disabled via theadd_self_loopsargument,e....
Multi-node multi-GPU training on ogbn-papers100M (examples/multi_gpu/papers100m_gcn_multinode.py) (#8070) Naive model parallelism on multiple GPUs (examples/multi_gpu/model_parallel.py) (#8309) Models Added the equivariant ViSNet from "ViSNet: an equivariant geometry-enhanced graph neural ne...