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.

A pytorch implementation of the paper Unsupervised Deep Embedding for Clustering Analysis.

Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation

This project is a scalable unified framework for deep graph clustering.

AAAI 2021-Deep Fusion Clustering Network

A very simple self-supervised image classification framework!

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.

Source code for E2DTC: An End to End Deep Trajectory Clustering Framework via Self-Training. ICDE 2021.

The code of AGCN (Attention-driven Graph Clustering Network), which is accepted by ACM MM 2021.

[BMVC2023] Official code for TEMI: Exploring the Limits of Deep Image Clustering using Pretrained Models

Code for Learning Embedding Space for Clustering From Deep Representations [IEEE BigData 2018]

Official implementation for [N2DCX] Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation

TensorFlow implementation of the Dissimilarity Mixture Autoencoder: https://arxiv.org/abs/2006.08177

[Accepted by TNNLS] Source Code for Relational Redundancy-Free Graph Clustering

The collection and reproduction code of the clustering methods I have known

PyTorch implementation of Self-training approch for short text clustering

GSCAN: Graph Stability Clustering using Edge-Aware Excess-of-Mass