Papers with Code 아카이브

Graph Embedding

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하위 태스크: 5
평가표: 1
보존된 평가 기록: 1

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

<span style="color:grey; opacity: 0.6">( Image credit: GAT )</span>

코드

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

https://github.com/ColdenChan/GAT_D

Graph Attention Networks

https://github.com/DavidLee-4032/Graph_Opt

Learning Combinatorial Optimization Algorithms over Graphs

https://github.com/DeepGraphLearning/graphvite

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding

https://github.com/DeepGraphLearning/pLogicNet

Probabilistic Logic Neural Networks for Reasoning

https://github.com/Diego999/pyGAT

Graph Attention Networks

https://github.com/EpiSci/SoCRATES

DeepSoCS: A Neural Scheduler for Heterogeneous System-on-Chip (SoC) Resource Scheduling

https://github.com/FranxYao/PoincareProbe

Poincaré Embeddings for Learning Hierarchical Representations

https://github.com/GraphEoM/GSCAN

Attributed Graph Clustering: A Deep Attentional Embedding Approach

https://github.com/GraphSAINT/GraphACT

GraphSAINT: Graph Sampling Based Inductive Learning Method

https://github.com/HazyResearch/KGEmb

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

https://github.com/HazyResearch/hgcn

Poincaré Embeddings for Learning Hierarchical Representations

https://github.com/HeapHop30/graph-attention-nets

Graph Attention Networks

https://github.com/HongyangGao/Graph-U-Nets

https://github.com/Hunter-DDM/InvTransE-and-InvRotatE

Inductively Representing Out-of-Knowledge-Graph Entities by Optimal Estimation Under Translational Assumptions

https://github.com/INK-USC/MHGRN

Modeling Relational Data with Graph Convolutional Networks

https://github.com/INK-USC/RE-Net

Modeling Relational Data with Graph Convolutional Networks

https://github.com/IllinoisGraphBenchmark/IGB-Datasets

Graph Attention Networks

https://github.com/JiabenLi/rgcn_paddlepaddle

Modeling Relational Data with Graph Convolutional Networks

https://github.com/JiaxuanYou/graph-generation

GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders

https://github.com/Junseok0207/M3S_Pytorch

Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels

https://github.com/KXY-PUBLIC/DiCGRL

Disentangle-based Continual Graph Representation Learning

https://github.com/KXY-PUBLIC/NASE

Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

https://github.com/Kaimaoge/IGNNK

Graph Attention Networks

https://github.com/Kristof-Neys/GAT_Neo4j_DGL

Graph Attention Networks

https://github.com/LARS-research/RelEns

Relation-aware Ensemble Learning for Knowledge Graph Embedding

https://github.com/LB0828/conve_reproduce

Convolutional 2D Knowledge Graph Embeddings

https://github.com/Lcrypto/EMD-Spectrum-LDPC

Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning

https://github.com/Lcrypto/Simulated-annealing-lifting-QC-LDPC

Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning

https://github.com/Lcrypto/classic-PEG-

Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning

https://github.com/Lcrypto/trapping-sets-enumeration

Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning

https://github.com/LoganZhao1997/last_mile_challenge

Learning Combinatorial Optimization Algorithms over Graphs

https://github.com/Loriba4/Lori-Baxter

Learning Combinatorial Optimization Algorithms over Graphs

https://github.com/MIRALab-USTC/GraphAKD

Rethinking Graph Convolutional Networks in Knowledge Graph Completion

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

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

https://github.com/MLDroid/graph2vec_tf

graph2vec: Learning Distributed Representations of Graphs

https://github.com/MS-Mind/MS-Code-01/tree/main/rotate

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

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