Graph Neural Network (GNN) based data-driven simulator which learns from PFEM simulation data. neural-simulator graph-neural-network scientific-machine-learning pfem Updated Oct 1, 2024 Fortran Improve this page Add a description, image, and links to the graph-neural-network topic page so tha...
GraphNeuralNetwork The Tools of the GraphNeuralNetwork 名称类型适用场景Github OpenNE 图表示学习 图节点表示学习,预训练 https://github.com/thunlp/OpenNE Graph_nets 图神经网络 基于关系模糊的图数据推理 https://github.com/deepmind/graph_nets DGL 图神经网络 建立图数据(可以无需通过networkx)并加载常用图...
[2] Graph Neural Network Model github.com/mtiezzi/gnn [3] Graph Neural Networks: A Review of Methods and Applications arxiv.org/abs/1812.0843 [4] Graphical-Based Learning Environments for Pattern Recognition link.springer.com/chapt [5] The Graph Neural Network Model ieeexplore.ieee.org/doc [...
Learning to Pre-train Graph Neural Networksojs.aaai.org/index.php/AAAI/article/view/16552#:~:text=Learning%20to%20Pre-train%20Graph%20Neural%20Networks%20%7C%20Proceedings,representations%20by%20recursively%20aggregating%20information%20from%20graph%20neighborhoods 代码地址: L2P-GNNgithub....
NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search 论文地址: https://openreview.net/pdf?id=bBff294gqLp 代码地址: https://github.com/THUMNLab/NAS-Bench-Graph 背景 神经网络架构搜索(NAS)作为自动机器学习(AutoML)的一个重要组成部分,旨在自动的搜索神经网络结构。NAS 的研究最早可以追溯到上世...
代码:https://github.com/cynricfu/MAGNN 摘要:大量现实世界的图或网络本质上是异构的,其中包含了多种类型的节点和连边关系。异构图嵌入是将异构图中丰富的结构和语义信息嵌入到网络节点的低维向量表示中。现有模型通常采用定义多个元路径的方式来捕捉其中的复合关系,并以此来指导邻居节点的选择。然而这些模型要么忽略...
1. Probabilistic Graph Neural Network(PGNN) 论文链接:https://grlearning.github.io/papers/135.pdf 1.1 任务描述 视觉理解是计算机视觉中一个很重要的任务,而过去的几年中,很多专家将这个问题归结成图像分类、对象检测等任务。然而,理解一个场景并不仅仅是识别场景中的物体,物体之间的相互关系也是很重要...
【1】Model_1: ChebNet(2016)-github-cnn_graph(tensorflow) cnn到任意图的推广 {Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering}具有快速局部光谱滤波的图卷上的卷积神经网络 【2】Model_2: 1stChebNet(2017)-github-gcn(tensorflow) ...
Recently, graph neural networks (GNN) have shown strength in learning low-dimensional representations of individual cells by propagating neighbor cell features and constructing cell-cell relations in a global cell graph9,10. For example, our in-house tool scGNN, a GNN model, has demonstrated superi...
https://github.com/Zhongdao/gcn_clustering/ Linkage Based Face Clustering via Graph Convolution Network Abstract 在本文中,我们为人脸聚类任务提出了一种精确和可扩展的方法。我们的目标是将一组人脸按照他们潜在的身份进行分组。我们将此任务表述为一个连接预测问题:如果两个人脸具有相同的身份,那么它们之间存在连...