Hypergraph Dynamic System (ICLR, 2024, Poster) [paper] Deep Temporal Graph Clustering (ICLR, 2024, Poster) [paper][code] GraphPulse: Topological representations for temporal graph property prediction (ICLR, 2024
IJCAI-19-Dynamic Hypergraph Neural Networks 动机 贡献 DHNN DHC(动态超图construction) 超图卷积 节点卷积 超边卷积 实验 Cora dataset Microblog 代码:https://github.com/iMoonLab/DHGNN 动机 超图/图的边是固有的,所以这个很大的限制了点之间的隐含关系。文章提出了动态超图神经网... 查看原文 论文笔记:IJCAI...
Dynamic Hypergraph Neural Networks (DHGNN) is a kind of neural networks modeling dynamically evolving hypergraph structures, which is composed of the stacked layers of two modules: dynamic hypergraph construction (DHG) and hypergrpah convolution (HGC). Considering initially constructed hypergraph is prob...
We proposed a novel and effective model named Dual Channel Representation-learning with Dynamic Intent Aggregation (DIA-DCR) to tackle the above problems. Specifically, we used the session graph and the global graph separately as inputs in the dual-channel structure. In the local channel, we imp...
Recently, batch-based image data representation has been demonstrated to be effective for context-enhanced image representation. The core issue for this ta
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs). - zxy-smart/Awesome-DynamicGraphLearning
(HGC). Considering initially constructed hypergraph is probably not a suitable representation for data, the DHG module dynamically updates hypergraph structure on each layer. Then hypergraph convolution is introduced to encode high-order data relations in a hypergraph structure. The HGC module includes ...