Open-source alternatives to Deepwalk

This project is a collection of deep learning research papers translated into annotated code. It serves as a resource for reproducing academic research, providing implementations of transformers, diffusion models, and reinforcement learning architectures. The library distinguishes itself by using a side-by-side annotation format that combines executable Python code with descriptive markdown notes. This approach provides a structured way to explain the logic of neural network papers alongside their PyTorch-based implementations. The codebase covers several major capability areas, including ge

Implementation of ComE algorithm

This repository provides a reference implementation of node2vec as described in the paper:

An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

A sparsity aware implementation of "Binarized Attributed Network Embedding" (ICDM 2018).

The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).

KDD 2022 The implementation for "Condensing Graphs via One-Step Gradient Matching" on graph classification is shown below. For node classification, please refer to link.

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

An implementation of "Community Preserving Network Embedding" (AAAI 2017)

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

The reference implementation of "Multi-scale Attributed Node Embedding". (Journal of Complex Networks 2021)

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).

A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).

The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".