Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch deep-learningartificial-intelligencegraph-neural-networkequivariance UpdatedDec 6, 2024 Python Representation-Learning-on-Heterogeneous-Graph machine-learningdeep-learningrepresentation-learningnetwork-embeddinggraph-embeddingheterogeneous-information-...
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Graph-neural-networks 图(graph)是一种数据格式,它可以用于表示社交网络、通信网络、蛋白分子网络等, 图中的节点表示网络中的个体,连边表示个体之间的连接关系。 许多机器学习任务例如社团发现、链路预测等都需要用到图结构数据, 因此图卷积神经网络的出现为这些问题的解决提供了新的思路。
Graph neural networks (GNNs) are rapidly advancing progress in ML for complex graph data applications. I've composed this concise recipe (i.e., studysheet) dedicated to students who are lookin to learn and keep up-to-date with GNNs. It's non-exhaustive but it aims to get students familia...
Graph Neural Networks: A Review of Methods and ApplicationsJie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Maosong Sun.2018paper Supervised neural networks for the classification of structuresA. Sperduti and A. Starita.IEEE Transactions on Neural Networks 1997.paper ...
Graph Neural Networks: A Review of Methods and ApplicationsJie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Maosong Sun.2018paper A Comprehensive Survey on Graph Neural Networks.Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu.2018paper ...
Graph Neural Networks: A Review of Methods and Applications. AI Open 2020. paper Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Maosong Sun. A Comprehensive Survey on Graph Neural Networks. arxiv 2019. paper Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhan...