https://github.com/jumxglhf/paretognn
공식 코드Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
Papers with Code 아카이브
Link Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
- 497
Link Prediction is a task in graph and network analysis where the goal is to predict missing or future connections between nodes in a network. Given a partially observed network, the goal of link prediction is to infer which links are most likely to be added or missing based on the observed connections and the structure of the network.
<span style="color:grey; opacity: 0.6">( Image credit: Inductive Representation Learning on Large Graphs )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jw9730/hot
공식 코드Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs
https://github.com/jw9730/lps
공식 코드Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
https://github.com/jwu4sml/grade
공식 코드https://github.com/kamigaito/acl2021kge
공식 코드https://github.com/karl-zhao/benchmarking-gnns-pyg
공식 코드https://github.com/kayzliu/tgtod
공식 코드TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale
https://github.com/kcacozhang/lgre
공식 코드Learning Granularity Representation for Temporal Knowledge Graph Completion
https://github.com/kckishan/HOGCN-LP
공식 코드Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks
https://github.com/kennthshang/cherry
공식 코드https://github.com/kgrl2021/submission-one
공식 코드A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
https://github.com/khushnood/TempNodeEmbed_upload
공식 코드TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix
https://github.com/kingsaint/InductiveExplainableLinkPrediction
공식 코드Explainable Link Prediction for Emerging Entities in Knowledge Graphs
https://github.com/kmswin1/comdense
공식 코드https://github.com/kmswin1/hplc
공식 코드Hierarchical Position Embedding of Graphs with Landmarks and Clustering for Link Prediction
https://github.com/kracr/document-level-relation-extraction
공식 코드Revisiting Document-Level Relation Extraction with Context-Guided Link Prediction
https://github.com/kracr/rcone-qa-mmkg
공식 코드RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphs
https://github.com/krr-oxford/boxsquaredel
공식 코드https://github.com/kthrn22/l-step
공식 코드Learnable Spatial-Temporal Positional Encoding for Link Prediction
https://github.com/kthrn22/ood-linker
공식 코드Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
https://github.com/ku21fan/coo-comic-onomatopoeia
공식 코드COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts
https://github.com/kumo-ai/ContextGNN
공식 코드https://github.com/lavis-nlp/irt2
공식 코드IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying Scale
https://github.com/lbq8942/tgacn
공식 코드Link-aware link prediction over temporal graph by pattern recognition
https://github.com/leapxcheng/rawnp
공식 코드https://github.com/leduckhai/wav2graph
공식 코드wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech
https://github.com/lemmonation/APNE
공식 코드Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective
https://github.com/lemmonation/G2-EMF
공식 코드Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective
https://github.com/leonyuhe/ctwalks
공식 코드https://github.com/leonyuhe/tlwalk
공식 코드https://github.com/leotrs/glee
공식 코드https://github.com/lequanlin/gnn-diff
공식 코드Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
https://github.com/lhrlab/hahe
공식 코드HAHE: Hierarchical Attention for Hyper-Relational Knowledge Graphs in Global and Local Level
https://github.com/ling-cai/time2box
공식 코드Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes
https://github.com/linhthi/ts
공식 코드Improving Graph Convolutional Networks with Transformer Layer in social-based items recommendation
https://github.com/lion-zs/gie
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.