The idea leads to a simple and efficient graph similarity, which we name Weisfeiler鈥揕eman similarity (WLS). In contrast to existing graph kernels, WLS is easy to implement with common deep learning frameworks. In graph classification experiments, transform-sum-cat significantly outperforms other ...
graph diffusion graph sampling 1.2.1 Edge Addition/Dropping 即 保留原始节点顺序,对邻接矩阵种的元进行改写。 基于图稀疏性(graph sparsification)的图结构优化方法 [8、9],基于图结构整洁性(graph sanitation)的方法 [3],以及图采样(graph sampling)。
Zhang Z, Cui P, Zhu W. Deep learning on graphs: A survey[J]. IEEE Transactions on Knowledge and Data Engineering, 2020. 18年的一篇GNN综述,读完之后,感觉GCN那一部分对我帮助还不小,帮我理清了脉络,也可能是因为之前把《Graph Representation Learning》这本书看完了,所以阅读过程还比较顺利。后面的VG...
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c
首先,使用图级表示技术(如Graph2Vec [144], FGSD[145])将数据库中的图编码到共享潜在空间中。然后,使用现成的异常值检测器来测量每个图的异常值。从本质上讲,这种方法需要对两个阶段的现有方法进行配对,但这两个阶段之间是相互分离的,因此,由于嵌入相似性不一定是为了异常检测而设计的,因此检测性能可能会很差...
高效K近邻图构建:W.Dong,C.Moses,andK.Li,“Efficientk-nearestneighborgraph construction for generic similarity measures,” in Proceedings of the 20th International Conference on World Wide Web, 2011, pp. 577–586. 高效K近邻图构建:C. Fu and D. Cai, “Efanna : An extremely fast approximate nea...
In this work, we aim to push further the integration of machine learning and combinatorial optimization, by proposing a new framework which combines deep neural networks with the best tools of “classical” metaheuristics for graph coloring, so as to solve very difficult graph coloring problems whic...
Focusing on the problems, we propose a leader-follower flocking algorithm based on a novel reinforcement learning (RL) model. We construct a homogeneous graph neural network (GNN) based multi-agent deep deterministic policy gradient (herein HGNN-MADDPG) algorithm model for multi-agent flocking ...
[WSDM 2021]Learning to Drop: Robust Graph Neural Network via Topological Denoising[Paper|Code] [WSDM 2021]Node Similarity Preserving Graph Convolutional Networks[Paper|Code] [IJCAI 2021]Understanding Structural Vulnerability in Graph Convolutional Networks[Paper|Code] ...
git clone https://github.com/DeepGraphLearning/graphvitecdgraphvite conda install -y --file conda/requirements.txt mkdir buildcdbuild&&cmake ..&&make&&cd-cdpython&&python setup.py install&&cd- On Colab !wget -c https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh!chmod +x...