SOTAVerified

Link Prediction

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.

( Image credit: Inductive Representation Learning on Large Graphs )

Papers

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Showing 201–250 of 1949 papers

TitleStatusHype
Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagationCode1
Decoupling the Depth and Scope of Graph Neural NetworksCode1
Reasoning Through Memorization: Nearest Neighbor Knowledge Graph EmbeddingsCode1
MGAE: Masked Autoencoders for Self-Supervised Learning on GraphsCode1
CHERRY: a Computational metHod for accuratE pRediction of virus-pRokarYotic interactions using a graph encoder-decoder modelCode1
Self-attention Presents Low-dimensional Knowledge Graph Embeddings for Link PredictionCode1
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoningCode1
TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge GraphsCode1
Pairwise Learning for Neural Link PredictionCode1
HGATE: Heterogeneous Graph Attention Auto-EncodersCode1
Poisoning Knowledge Graph Embeddings via Relation Inference PatternsCode1
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution MethodsCode1
Parallel Training of Knowledge Graph Embedding Models: A Comparison of TechniquesCode1
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic ConesCode1
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph EmbeddingCode1
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector QuantizationCode1
Meta-Knowledge Transfer for Inductive Knowledge Graph EmbeddingCode1
A Probabilistic Framework for Knowledge Graph Data AugmentationCode1
A Broader Picture of Random-walk Based Graph EmbeddingCode1
Drug Similarity and Link Prediction Using Graph Embeddings on Medical Knowledge GraphsCode1
Boosting Graph Embedding on a Single GPUCode1
GRAPE for Fast and Scalable Graph Processing and random walk-based EmbeddingCode1
Neural Link Prediction with Walk PoolingCode1
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph RepresentationsCode1
Benchmarking Graph Neural Networks on Dynamic Link PredictionCode1
How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence ViewCode1
SAFRAN: An interpretable, rule-based link prediction method outperforming embedding modelsCode1
Graph Algorithms for Multiparallel Word AlignmentCode1
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph ForecastingCode1
Knowledge Perceived Multi-modal Pretraining in E-commerceCode1
Variational Graph Normalized Auto-EncodersCode1
Global Self-Attention as a Replacement for Graph ConvolutionCode1
Fuzzy Logic Based Logical Query Answering on Knowledge GraphsCode1
Cold Start Similar Artists Ranking with Gravity-Inspired Graph AutoencodersCode1
Relational Graph Convolutional Networks: A Closer LookCode1
A Survey on Role-Oriented Network EmbeddingCode1
Improving Inductive Link Prediction Using Hyper-Relational FactsCode1
Universal Multilayer Network Exploration by Random Walk with RestartCode1
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic SpaceCode1
Edge Proposal Sets for Link PredictionCode1
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge GraphsCode1
Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical StudyCode1
Query Embedding on Hyper-relational Knowledge GraphsCode1
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link PredictionCode1
DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object TrackingCode1
Pseudo-Riemannian Graph Convolutional NetworksCode1
Learning from Counterfactual Links for Link PredictionCode1
Multiresolution Equivariant Graph Variational AutoencoderCode1
Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector EmbeddingsCode1
How Attentive are Graph Attention Networks?Code1
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All datasetsFB15k-237WN18RRWN18FB15kYAGO3-10ICEWS05-15ICEWS14CiteseerCoraPubmedWikidata5MGDELT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoKGEHits@100.56—Unverified
2CP-N3-RPHits@100.55—Unverified
3DistMult (after variational EM)Hits@100.55—Unverified
4KG-R3Hits@100.54—Unverified
5LASSHits@100.53—Unverified
6MDE_advHits@100.53—Unverified
7GFA-NNHits@100.52—Unverified
8KGRefinerHits@100.49—Unverified
9ComplEx NSCachingHits@100.48—Unverified
10LogicENNHits@100.47—Unverified
#ModelMetricClaimedVerifiedStatus
1MoCoKGCHits@100.88—Unverified
2KERMITHits@100.83—Unverified
3MoCoSAHits@100.82—Unverified
4SimKGCIB(+PB+SN)Hits@100.82—Unverified
5C-LMKE(bert-base)Hits@100.79—Unverified
6LASSHits@100.79—Unverified
7LP-BERTHits@100.75—Unverified
8KGLMHits@100.74—Unverified
9StAR(Self-Adp)Hits@100.71—Unverified
10PALTHits@100.69—Unverified
#ModelMetricClaimedVerifiedStatus
1OpenKE (han2018openke)training time (s)11—Unverified
2LibKGE (ruffinelli2020you)training time (s)10—Unverified
3GraphVite (zhu2019graphvite)training time (s)6—Unverified
4Inverse ModelHits@100.96—Unverified
5QuatDEHits@100.96—Unverified
6LineaREHits@100.96—Unverified
7AutoKGEHits@100.96—Unverified
8MEI (small)Hits@100.96—Unverified
9ComplEx-N3 (reciprocal)Hits@100.96—Unverified
10RotatEHits@100.96—Unverified
#ModelMetricClaimedVerifiedStatus
1OPTransEHits@100.9—Unverified
2AutoKGEMRR0.86—Unverified
3ComplEx-N3 (reciprocal)MRR0.86—Unverified
4LineaREMRR0.84—Unverified
5DistMult (after variational EM)MRR0.84—Unverified
6QuatEMRR0.83—Unverified
7SEEKMRR0.83—Unverified
8MEI-BTDMRR0.81—Unverified
9MEI (small)MRR0.8—Unverified
10pRotatEMRR0.8—Unverified