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Graph Representation Learning

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The goal of Graph Representation Learning is to construct a set of features (‘embeddings’) representing the structure of the graph and the data thereon. We can distinguish among Node-wise embeddings, representing each node of the graph, Edge-wise embeddings, representing each edge in the graph, and Graph-wise embeddings representing the graph as a whole.

Source: SIGN: Scalable Inception Graph Neural Networks

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Gaoyiminggithub/Graphonomy-Panoptic

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Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

https://github.com/GoloMarcos/JMLR-OLGA

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OLGA: One-cLass Graph Autoencoder

https://github.com/Graph-COM/SUREL_Plus

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SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning

https://github.com/GraphSAINT/GraphSAINT

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GraphSAINT: Graph Sampling Based Inductive Learning Method

https://github.com/HCPLab-SYSU/SSGRL

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Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition

https://github.com/HELL-TO-HEAVEN/KGE-CL

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KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings

https://github.com/HKUST-KnowComp/FKGE

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Differentially Private Federated Knowledge Graphs Embedding

https://github.com/HW-HaoWang/DHC-E

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Hyperparameter-free and Explainable Whole Graph Embedding

https://github.com/Hope-Rita/EDGPAT

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Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction

https://github.com/IBM/AMLSim

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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

https://github.com/IBM/EvolveGCN

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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

https://github.com/JC-202/MMP

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Memory-based Message Passing: Decoupling the Message for Propogation from Discrimination

https://github.com/JD-AI-Research-Silicon-Valley/SACN

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End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

https://github.com/JasonZhujp/RELIEF

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RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning

https://github.com/JeanKaddour/WASAM

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When Do Flat Minima Optimizers Work?

https://github.com/JunLLuo/DeFi-similarity

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Investigating Similarities Across Decentralized Financial (DeFi) Services

https://github.com/JunLLuo/Illicit-node-detect-PU-Learning

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Towards Improved Illicit Node Detection with Positive-Unlabelled Learning

https://github.com/LCS2-IIITD/Hyphen

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Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification

https://github.com/LJeub/Local2Global_embedding

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Local2Global: Scaling global representation learning on graphs via local training

https://github.com/LemonNoel/ATransN

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An Adversarial Transfer Network for Knowledge Representation Learning

https://github.com/LinXueyuanStdio/EchoEA

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EchoEA: Echo Information between Entities and Relations for Entity Alignment

https://github.com/LivNLP/Relational-Walk-for-Knowledge-Graphs

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RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding

https://github.com/MIRALab-USTC/KGE-HAKE

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Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

https://github.com/MaKaili/Contrast-Reg

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Calibrating and Improving Graph Contrastive Learning

https://github.com/Maysir/GEM-GCN

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Knowledge Embedding Based Graph Convolutional Network

https://github.com/Microsoft/Graphormer

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Do Transformers Really Perform Bad for Graph Representation?

https://github.com/Monash-NeuroAI/Deep-Spatiotemporal-Variational-Bayes

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A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

https://github.com/NIVA-Knowledge-Graph/TERA

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Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

https://github.com/NYXFLOWER/GripNet

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GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs

https://github.com/OceanskySun/GraftNet

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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text

https://github.com/OneForward/UniGNN

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UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks

https://github.com/PaddlePaddle/PGL

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Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems

https://github.com/PaddlePaddle/Research

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CoKE: Contextualized Knowledge Graph Embedding

https://github.com/PaddlePaddle/models

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CoKE: Contextualized Knowledge Graph Embedding

https://github.com/PangYunsheng8/CGIPool

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Graph Pooling via Coarsened Graph Infomax

https://github.com/PurdueMINDS/size-invariant-GNNs

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Size-Invariant Graph Representations for Graph Classification Extrapolations

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