https://github.com/763337092/LP-BERT
공식 코드Multi-task Pre-training Language Model for Semantic Network Completion
Papers with Code 아카이브
Knowledge Graph Embedding
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AKSW/KG2Vec
공식 코드https://github.com/Accenture/AmpliGraph
공식 코드Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes
https://github.com/AnselCmy/FedE
공식 코드https://github.com/AutoML-4Paradigm/ERAS
공식 코드Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding
https://github.com/AutoML-4Paradigm/Interstellar
공식 코드Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding
https://github.com/AutoML-4Paradigm/NSCaching
공식 코드Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding
https://github.com/AutoML-Research/AutoSF
공식 코드Bilinear Scoring Function Search for Knowledge Graph Learning
https://github.com/DeMix2023/Demix
공식 코드Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding
https://github.com/DeepGraphLearning/KnowledgeGraphEmbedding
공식 코드RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/Ebiquity/KGFP
공식 코드Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization
https://github.com/Elric2718/Bayes_Embedding
공식 코드https://github.com/Erik-BM/NIVAUC
공식 코드Knowledge Graph Embedding for Ecotoxicological Effect Prediction
https://github.com/HELL-TO-HEAVEN/KGE-CL
공식 코드KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
https://github.com/HKUST-KnowComp/FKGE
공식 코드https://github.com/JD-AI-Research-Silicon-Valley/SACN
공식 코드End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion
https://github.com/LemonNoel/ATransN
공식 코드An Adversarial Transfer Network for Knowledge Representation Learning
https://github.com/LinXueyuanStdio/EchoEA
공식 코드EchoEA: Echo Information between Entities and Relations for Entity Alignment
https://github.com/LivNLP/Relational-Walk-for-Knowledge-Graphs
공식 코드RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding
https://github.com/MIRALab-USTC/KGE-HAKE
공식 코드Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/Maysir/GEM-GCN
공식 코드https://github.com/NIVA-Knowledge-Graph/TERA
공식 코드Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings
https://github.com/PaddlePaddle/Research
공식 코드https://github.com/PaddlePaddle/models
공식 코드https://github.com/Pzoom522/ProcrustEs-KGE
공식 코드Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
https://github.com/Sujit-O/pykg2vec
공식 코드https://github.com/Wentao-Xu/SEEK
공식 코드https://github.com/ZihengZZH/OntoEA
공식 코드OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embedding
https://github.com/abachaa/evaluationmetrics-acl23
공식 코드An Investigation of Evaluation Metrics for Automated Medical Note Generation
https://github.com/adaruna3/continual-kge
공식 코드https://github.com/adaruna3/explainable-kge
공식 코드https://github.com/aistairc/RDF-star2Vec
공식 코드https://github.com/aistairc/kgrc-rdf-star
공식 코드https://github.com/akirato/perm-gaussiankg
공식 코드Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
https://github.com/alejgh/wikidata-edithist-refinement
공식 코드Leveraging Wikidata's edit history in knowledge graph refinement tasks
https://github.com/alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
공식 코드PairRE: Knowledge Graph Embeddings via Paired Relation Vectors
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.