Representation learning on large graphs using stochastic graph convolutions.
Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)
Representation-Learning-on-Heterogeneous-Graph
A collection of important graph embedding, classification and representation learning papers with implementations.
翻译 - 一系列重要的图形嵌入，分类和表示学习论文以及实现。
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
翻译 - 用于知识图表示学习的Python库https://docs.ampligraph.org
A curated list for awesome graph representation learning resources.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
Graph Representation Learning
hypergraph representation learning, graph neural network
Representation learning on large graphs using stochastic graph convolutions.
Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
Multi-view Graph Contrastive Representation Learning for Drug-drug Interaction Prediction
🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
Representation and learning framework for dynamic graphs using Graph Neural Networks.
source code of IJCAI 2021 paper "Graph Representation with Curriculum Contrastive Learning"
PyTorch version for the "Micro-expression Recognition Based on Facial Graph Representation Learning and Facial Action Unit Fusion"
[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)
Source code and dataset for KDD 2020 paper "Understanding Negative Sampling in Graph Representation Learning"