Papers with Code 아카이브
Knowledge Graph Completion
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Knowledge graphs $G$ are represented as a collection of triples $\\{(h, r, t)\\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dice-group/dice-embeddings
공식 코드https://github.com/dice-group/universal_embeddings
공식 코드https://github.com/duyguislakoglu/temt
공식 코드https://github.com/dwslab/jRDF2Vec
공식 코드RDF2Vec Light -- A Lightweight Approach for Knowledge Graph Embeddings
https://github.com/facebookresearch/fastText
공식 코드https://github.com/facebookresearch/ssl-relation-prediction
공식 코드https://github.com/fedelopez77/gyrospd
공식 코드Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
https://github.com/genggengcss/OntoZSL
공식 코드https://github.com/genggengcss/pdkgc
공식 코드Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model
https://github.com/glaciohound/lerp
공식 코드Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
https://github.com/google-research/smore
공식 코드SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
https://github.com/graphcore-research/kg-topology-toolbox
공식 코드The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models
https://github.com/graphcore/distributed-kge-poplar
공식 코드BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion
https://github.com/graphpku/open-world-kg
공식 코드Rethinking Knowledge Graph Evaluation Under the Open-World Assumption
https://github.com/guilhermesfc/ontology-matching-absolute-orientation
공식 코드Ontology Matching Through Absolute Orientation of Embedding Spaces
https://github.com/guojiapub/bique
공식 코드https://github.com/harryshomer/kg-mixup
공식 코드Toward Degree Bias in Embedding-Based Knowledge Graph Completion
https://github.com/harryshomer/quad
공식 코드Learning Representations for Hyper-Relational Knowledge Graphs
https://github.com/harryshomer/tagnet
공식 코드Distance-Based Propagation for Efficient Knowledge Graph Reasoning
https://github.com/haseebs/OWE
공식 코드An Open-World Extension to Knowledge Graph Completion Models
https://github.com/hipgraph/sptransx
공식 코드https://github.com/hkust-knowcomp/complexhyperbolickge
공식 코드Complex Hyperbolic Knowledge Graph Embeddings with Fast Fourier Transform
https://github.com/hkust-knowcomp/mico
공식 코드MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation
https://github.com/hmthanh/GCAT
공식 코드Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
https://github.com/honggen-zhang/hasa-ckge
공식 코드HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding
https://github.com/hopkin-ghp/QuatDE
공식 코드QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion
https://github.com/hou27/recdap-fkgc
공식 코드https://github.com/hse-cs/migtf
공식 코드Knowledge Graph Completion with Mixed Geometry Tensor Factorization
https://github.com/huda-hakami/learning-to-borrow-for-kgs
공식 코드https://github.com/hwwang55/PathCon
공식 코드https://github.com/hyleepp/continue-kgc
공식 코드https://github.com/hyu-nlp/hyper-cl
공식 코드Hyper-CL: Conditioning Sentence Representations with Hypernetworks
https://github.com/i40-Tools/I40KG-Embeddings
공식 코드Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings
https://github.com/ibalazevic/HypER
공식 코드https://github.com/ibalazevic/TuckER
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.