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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/Pzoom522/ProcrustEs-KGE

공식 코드

Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis

https://github.com/RingBDStack/MinGE

공식 코드

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks

https://github.com/RingBDStack/SUGAR

공식 코드

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

https://github.com/SBrandeis/k-core-embedding

공식 코드

About Graph Degeneracy, Representation Learning and Scalability

https://github.com/SamJia/CommunityGAN

공식 코드

CommunityGAN: Community Detection with Generative Adversarial Nets

https://github.com/Somedaywilldo/AutoGCL

공식 코드

AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators

https://github.com/SsGood/ADGCN

공식 코드

Adversarial Graph Disentanglement

https://github.com/SsGood/DBGAN

공식 코드

Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning

https://github.com/Sujit-O/pykg2vec

공식 코드

Pykg2vec: A Python Library for Knowledge Graph Embedding

https://github.com/THUDM/GCC

공식 코드

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

https://github.com/THUDM/cogdl

공식 코드

CogDL: A Comprehensive Library for Graph Deep Learning

https://github.com/TemporalKGTeam/xERTE

공식 코드

xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links

https://github.com/TommyDzh/RingFormer

공식 코드

RingFormer: A Ring-Enhanced Graph Transformer for Organic Solar Cell Property Prediction

https://github.com/Wei9711/NegGCNs

공식 코드

Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes

https://github.com/Wentao-Xu/SEEK

공식 코드

SEEK: Segmented Embedding of Knowledge Graphs

https://github.com/XiaoxinHe/Graph-ViT-MLPMixer

공식 코드

A Generalization of ViT/MLP-Mixer to Graphs

https://github.com/XiaoxinHe/TAPE

공식 코드

Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

https://github.com/Xin-Cheng-Wen/RepoSPD

공식 코드

Repository-Level Graph Representation Learning for Enhanced Security Patch Detection

https://github.com/Xovee/ccgl

공식 코드

CCGL: Contrastive Cascade Graph Learning

https://github.com/YKQ98/Matformer

공식 코드

Periodic Graph Transformers for Crystal Material Property Prediction

https://github.com/YuGuangWang/FGT

공식 코드

Decimated Framelet System on Graphs and Fast G-Framelet Transforms

https://github.com/Zhaoyang-Chu/HGRL-DTA

공식 코드

Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding Affinity

https://github.com/Zhhuizhe/GT-SVQ

공식 코드

GT-SVQ: A Linear-Time Graph Transformer for Node Classification Using Spiking Vector Quantization

https://github.com/ZihengZZH/OntoEA

공식 코드

OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embedding

https://github.com/a-hou/gtca

공식 코드

GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning

https://github.com/aalto-quml/pipe

공식 코드

Positional Encoding meets Persistent Homology on Graphs

https://github.com/abachaa/evaluationmetrics-acl23

공식 코드

An Investigation of Evaluation Metrics for Automated Medical Note Generation

https://github.com/abbahaddou/CGSO

공식 코드

Centrality Graph Shift Operators for Graph Neural Networks

https://github.com/adaruna3/continual-kge

공식 코드

Continual Learning of Knowledge Graph Embeddings

https://github.com/adaruna3/explainable-kge

공식 코드

Explainable Knowledge Graph Embedding: Inference Reconciliation for Knowledge Inferences Supporting Robot Actions

https://github.com/ahachang/defend

공식 코드

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement

https://github.com/ahmadihafez/ConvDySAT

공식 코드

ConvDySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention and Convolutional Neural Networks

https://github.com/ahmedesamy/dsgrl

공식 코드

Data-Driven Self-Supervised Graph Representation Learning

https://github.com/aidos-lab/Diss-l-ECT

공식 코드

Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms

https://github.com/air029/polyformer

공식 코드

PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer

https://github.com/aistairc/RDF-star2Vec

공식 코드

RDF-star2Vec: RDF-star Graph Embeddings for Data Mining

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.