https://github.com/HarryShomer/Better-Inductive-KGC
공식 코드Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
Papers with Code 아카이브
Knowledge Graphs
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A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Hippopotamus0308/SSTKG
공식 코드https://github.com/IBM/Open-KG-canonicalization
공식 코드Open Knowledge Graphs Canonicalization using Variational Autoencoders
https://github.com/IBM/RuDaS
공식 코드RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools
https://github.com/IBM/retrieve-write-slot-filling
공식 코드https://github.com/IBM/wikicausal
공식 코드WikiCausal: Corpus and Evaluation Framework for Causal Knowledge Graph Construction
https://github.com/IDEA-FinAI/Simple-HHEA
공식 코드https://github.com/INDElab/rgvae
공식 코드Knowledge Generation -- Variational Bayes on Knowledge Graphs
https://github.com/INK-USC/CALM
공식 코드Pre-training Text-to-Text Transformers for Concept-centric Common Sense
https://github.com/INK-USC/DArtNet
공식 코드Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
https://github.com/INK-USC/HGN
공식 코드Learning Contextualized Knowledge Structures for Commonsense Reasoning
https://github.com/INK-USC/KagNet
공식 코드KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
https://github.com/INK-USC/MHGRN
공식 코드Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering
https://github.com/INK-USC/RE-Net
공식 코드Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
https://github.com/INK-USC/SalKG
공식 코드SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning
https://github.com/INK-USC/deceive-KG-models
공식 코드Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
https://github.com/Ipazia-AI/latent-explorer
공식 코드Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph
https://github.com/JD-AI-Research-Silicon-Valley/SACN
공식 코드End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion
https://github.com/JeanKaddour/WASAM
공식 코드https://github.com/Jeff20100601/GHNN_clean
공식 코드Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs
https://github.com/Jeffrey-Sardina/TWIG-I
공식 코드https://github.com/Jeffrey-Sardina/TWIG-TWM-dev
공식 코드https://github.com/JerichoWorld/JerichoWorld
공식 코드https://github.com/JiapengWu/TeMP
공식 코드TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
https://github.com/JiapengWu/Time-Aware-Incremental-Embedding
공식 코드TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
https://github.com/JiaweiSheng/FAAN
공식 코드Adaptive Attentional Network for Few-Shot Knowledge Graph Completion
https://github.com/JingruG/GATHER
공식 코드Open-Set Knowledge-Based Visual Question Answering with Inference Paths
https://github.com/JinheonBaek/GEN
공식 코드Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
https://github.com/Juanhui28/Are_MPNNs_helpful
공식 코드Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
https://github.com/JunhengH/joie-kdd19
공식 코드https://github.com/KGQA/KGQA-datasets-generalization
공식 코드https://github.com/KRR-Oxford/DeepOnto
공식 코드Contextual Semantic Embeddings for Ontology Subsumption Prediction
https://github.com/KRR-Oxford/OWL2Vec-Star
공식 코드https://github.com/KnowledgeCaptureAndDiscovery/OBA
공식 코드OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphs
https://github.com/KokiKishimoto/cp_decomposition
공식 코드https://github.com/KokiKishimoto/cp_decomposition_alpha
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.