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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/thiviyant/intelligraphs

공식 코드

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation

https://github.com/thunlp/opengcl

공식 코드

Evaluating Modules in Graph Contrastive Learning

https://github.com/tianyufan0504/was

공식 코드

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks

https://github.com/timpostuvan/CTDG-link-anomaly-detection

공식 코드

Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs

https://github.com/timpostuvan/tgb-link-anomaly-detection-baselines

공식 코드

Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs

https://github.com/tonyauyeung/local2gae2global

공식 코드

L2G2G: a Scalable Local-to-Global Network Embedding with Graph Autoencoders

https://github.com/topgunlcs98/scrl

공식 코드

Self-supervised Consensus Representation Learning for Attributed Graph

https://github.com/topologicalpooling/TopologicalPool

공식 코드

Topological Pooling on Graphs

https://github.com/torchkge-team/torchkge

공식 코드

TorchKGE: Knowledge Graph Embedding in Python and PyTorch

https://github.com/tranhungnghiep/AnalyzeKGE

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Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective

https://github.com/tranhungnghiep/KG20C

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Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space

https://github.com/tranhungnghiep/MEI-KGE

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Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion

https://github.com/tranhungnghiep/meim-kge

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MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction

https://github.com/triplej0079/deepim

공식 코드

Deep Graph Representation Learning and Optimization for Influence Maximization

https://github.com/twitter-research/lmsoc

공식 코드

LMSOC: An Approach for Socially Sensitive Pretraining

https://github.com/twitter-research/sign

공식 코드

SIGN: Scalable Inception Graph Neural Networks

https://github.com/udel-cbcb/triple_walk

공식 코드

A knowledge graph representation learning approach to predict novel kinase-substrate interactions

https://github.com/uestc-lese/spgrl

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Structure-Preserving Graph Representation Learning

https://github.com/uestclbh/pc-conv

공식 코드

PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering

https://github.com/uma-pi1/grash

공식 코드

Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings

https://github.com/uma-pi1/kgt5-context

공식 코드

Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction

https://github.com/upperr/DLSM

공식 코드

A Deep Latent Space Model for Graph Representation Learning

https://github.com/user683/CausalDiffRec

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Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation

https://github.com/venomouscyanide/s3grl

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Simplifying Subgraph Representation Learning for Scalable Link Prediction

https://github.com/venomouscyanide/s3grl_ogb

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Simplifying Subgraph Representation Learning for Scalable Link Prediction

https://github.com/ventr1c/res-gcl

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Certifiably Robust Graph Contrastive Learning

https://github.com/vermouthdky/simteg

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SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

https://github.com/vinhsuhi/wge

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Two-view Graph Neural Networks for Knowledge Graph Completion

https://github.com/violet24k/sphere

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SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval

https://github.com/vuptran/graph-representation-learning

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Learning to Make Predictions on Graphs with Autoencoders

https://github.com/waimorris/E-GraphSAGE

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E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT

https://github.com/wangpf3/LAN

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Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding

https://github.com/wattpad/gatas

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Graph Representation Learning Network via Adaptive Sampling

https://github.com/wdimmy/graphretrieval

공식 코드

An Empirical Study of Retrieval-enhanced Graph Neural Networks

https://github.com/weihua916/powerful-gnns

공식 코드

How Powerful are Graph Neural Networks?

https://github.com/weiyifan1023/MVGE

공식 코드

Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning Question

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