Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
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Updated
Jun 23, 2024 - Python
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Structural Deep Clustering Network
[AAAI 2023] An official source code for paper Hard Sample Aware Network for Contrastive Deep Graph Clustering.
[AAAI 2022] An official source code for paper Deep Graph Clustering via Dual Correlation Reduction.
Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation
Papers for Open Knowledge Discovery
A pytorch implementation of the paper Unsupervised Deep Embedding for Clustering Analysis.
Graph Agglomerative Clustering (GAC) toolbox
This project is a scalable unified framework for deep graph clustering.
Source code for E2DTC: An End to End Deep Trajectory Clustering Framework via Self-Training. ICDE 2021.
Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of variational autoencoders to find multiple disentangled clusterings of data.
Author implementation of deep clustering model from the paper "Learning Embedding Space for Clustering From Deep Representations".
AAAI 2021-Deep Fusion Clustering Network
Graph Agglomerative Clustering Library
A very simple self-supervised image classification framework!
TensorFlow implementation of the Dissimilarity Mixture Autoencoder: https://arxiv.org/abs/2006.08177
The code of AGCN (Attention-driven Graph Clustering Network), which is accepted by ACM MM 2021.
DIVA: A Dirichlet Process Mixtures Based Incremental Deep Clustering Algorithm via Variational Auto-Encoder
[Accepted by TNNLS] Source Code for Relational Redundancy-Free Graph Clustering
GSCAN: Graph Stability Clustering using Edge-Aware Excess-of-Mass
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