Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

The source code of the paper "Improved Topology Features for Node Classification on Heterophilic Graphs"

SIGMOD 2024 paper titled "Efficient High-Quality Clustering for Large Bipartite Graphs"

the official implementation of KDD2024 paper "Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks"

Massive Sparse Data Clustering Based on Frequent Items (SIGMOD 2023)

gnn for link prediction，图神经网络用于链接预测。

TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification

Dynamic Dual Gating Neural Networks, ICCV 2021

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Analysis by Synthesis — reimplemented

📚 Solutions to Introduction to Algorithms Third Edition

A repository for conditional computation

Dynamic-Neural-Network-Decoupling

PyTorch implementation of SENet

GPT-3: Language Models are Few-Shot Learners

Multi-layer convolutional LSTM with Pytorch