https://github.com/AutoML-Research/AutoSF
공식 코드Bilinear Scoring Function Search for Knowledge Graph Learning
Papers with Code 아카이브
Link Property Prediction
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Barcavin/efficient-node-labelling
공식 코드Pure Message Passing Can Estimate Common Neighbor for Link Prediction
https://github.com/CUAI/Edge-Proposal-Sets
공식 코드https://github.com/DM2-ND/CFLP
공식 코드https://github.com/DeepGraphLearning/KnowledgeGraphEmbedding
공식 코드RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/DeepGraphLearning/NBFNet
공식 코드Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
https://github.com/Graph-COM/SUREL_Plus
공식 코드SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning
https://github.com/GraphPKU/NeuralCommonNeighbor
공식 코드https://github.com/GraphSAINT/GraphSAINT
공식 코드https://github.com/aditya-grover/node2vec
공식 코드https://github.com/alibaba/graph-gpt
공식 코드GraphGPT: Graph Learning with Generative Pre-trained Transformers
https://github.com/alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
공식 코드PairRE: Knowledge Graph Embeddings via Paired Relation Vectors
https://github.com/april-tools/gekcs
공식 코드How to Turn Your Knowledge Graph Embeddings into Generative Models
https://github.com/astroming/GNNHE
공식 코드Can GNNs Learn Link Heuristics? A Concise Review and Evaluation of Link Prediction Methods
https://github.com/cf020031308/mad-learning
공식 코드https://github.com/deepgraphlearning/astarnet
공식 코드A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
https://github.com/dellixx/transerr
공식 코드TransERR: Translation-based Knowledge Graph Embedding via Efficient Relation Rotation
https://github.com/devnkong/VQ-GNN
공식 코드VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
https://github.com/facebookresearch/SEAL_OGB
공식 코드Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning
https://github.com/facebookresearch/ssl-relation-prediction
공식 코드https://github.com/google-research/google-research
공식 코드Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
https://github.com/graph-com/surel
공식 코드Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning
https://github.com/graphpku/refined-gae
공식 코드https://github.com/hongluzhou/dhypr
공식 코드https://github.com/hzli-ucas/stargraph
공식 코드StarGraph: Knowledge Representation Learning based on Incomplete Two-hop Subgraph
https://github.com/lars-research/relens
공식 코드Relation-aware Ensemble Learning for Knowledge Graph Embedding
https://github.com/lrlbbzl/unibi_ogb
공식 코드https://github.com/migalkin/NodePiece
공식 코드NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
https://github.com/snap-stanford/ogb
공식 코드Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/temporal-graphs-negative-sampling/tgb
공식 코드Temporal graph models fail to capture global temporal dynamics
https://github.com/tewiSong/Rot-Pro
공식 코드Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding
https://github.com/tkipf/pygcn
공식 코드Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/ttrouill/complex
공식 코드https://github.com/venomouscyanide/s3grl
공식 코드Simplifying Subgraph Representation Learning for Scalable Link Prediction
https://github.com/venomouscyanide/s3grl_ogb
공식 코드Simplifying Subgraph Representation Learning for Scalable Link Prediction
https://github.com/williamleif/GraphSAGE
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.