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Feb 20, 2020 · We design a specific GAE-based model for graph clustering to be consistent with the theory, namely Embedding Graph Auto-Encoder (EGAE).
A novel joint clustering method, which combines relaxed k-means and spectral clustering and is applicable for the learned embedding is developed, namely, ...
Feb 20, 2020 · In this paper, we propose a graph convolution network based clustering model, namely, Embedding Graph Auto-Encoder with JOint Clustering via ...
hyzhang98/EGAE: Implementation of "Embedding Graph Auto-Encoder for ...
github.com › hyzhang98 › EGAE
This repository is our implementation of Hongyuan Zhang, Pei Li, Rui Zhang, and Xuelong Li, "Embedding Graph Auto-Encoder for Graph Clustering," IEEE ...
Sep 28, 2024 · It fuses relaxed Kmeans and spectral clustering to get clusters, and the adjacency is shared by both GAE and joint clustering. ... Deep ...
Most recent graph clustering methods have resorted to Graph Auto-Encoders (GAEs) to perform joint clustering and embedding learning.
In this paper, we introduce a novel graph node clustering method with an improved graph variational auto-encoder method based on VGAE.
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Aug 16, 2024 · L-L-K-E0: It utilizes two layers of linear transformation as the encoder and performs clustering on the embeddings using the k-means algorithm.
Mar 13, 2021 · Graph clustering, aiming to partition nodes of a graph into various groups via an unsupervised approach, is an attractive topic in recent ...
Jun 10, 2020 · 本文用GNN来学习适合于聚类任务的节点表示. 比较特别的是,本文同时考虑了K-Mean聚类和谱聚类来实现更好的聚类.提出了Embedding Graph Auto-Encoder ...