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

Showing 301350 of 1949 papers

TitleStatusHype
Adaptive Attentional Network for Few-Shot Knowledge Graph CompletionCode1
Predicting Biomedical Interactions with Higher-Order Graph Convolutional NetworksCode1
Inductive Entity Representations from Text via Link PredictionCode1
Probabilistic Case-based Reasoning for Open-World Knowledge Graph CompletionCode1
Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix FactorizationCode1
TeRo: A Time-aware Knowledge Graph Embedding via Temporal RotationCode1
LibKGE - A knowledge graph embedding library for reproducible researchCode1
Multi-Relational Embedding for Knowledge Graph Representation and AnalysisCode1
Learning Graph Normalization for Graph Neural NetworksCode1
Message Passing for Hyper-Relational Knowledge GraphsCode1
Force2Vec: Parallel force-directed graph embeddingCode1
CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkCode1
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learningCode1
Understanding Coarsening for Embedding Large-Scale GraphsCode1
Hierarchical Message-Passing Graph Neural NetworksCode1
TorchKGE: Knowledge Graph Embedding in Python and PyTorchCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
Adversarial Privacy Preserving Graph Embedding against Inference AttackCode1
HittER: Hierarchical Transformers for Knowledge Graph EmbeddingsCode1
LowFER: Low-rank Bilinear Pooling for Link PredictionCode1
MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approachCode1
Relational Reflection Entity AlignmentCode1
Convolutional Complex Knowledge Graph EmbeddingsCode1
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous NetworksCode1
Second-Order Pooling for Graph Neural NetworksCode1
PanRep: Graph neural networks for extracting universal node embeddings in heterogeneous graphsCode1
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous GraphsCode1
Inductive Link Prediction for Nodes Having Only Attribute InformationCode1
BoxE: A Box Embedding Model for Knowledge Base CompletionCode1
Learning Reasoning Strategies in End-to-End Differentiable ProvingCode1
Graph Convolutional Networks for Graphs Containing Missing FeaturesCode1
Generalizing Tensor Decomposition for N-ary Relational Knowledge BasesCode1
Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural NetworksCode1
Simple and Deep Graph Convolutional NetworksCode1
Adaptive Graph Encoder for Attributed Graph EmbeddingCode1
Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base EmbeddingsCode1
Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link PredictionCode1
Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph CompletionCode1
Space-Time Correspondence as a Contrastive Random WalkCode1
Self-supervised edge features for improved Graph Neural Network trainingCode1
A Self-Attention Network based Node Embedding ModelCode1
GCC: Graph Contrastive Coding for Graph Neural Network Pre-TrainingCode1
Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link PredictionCode1
Persona2vec: A Flexible Multi-role Representations Learning Framework for GraphsCode1
Understanding Negative Sampling in Graph Representation LearningCode1
Fast Network Embedding Enhancement via High Order Proximity ApproximationCode1
SEEK: Segmented Embedding of Knowledge GraphsCode1
You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph EmbeddingsCode1
Explainable Link Prediction for Emerging Entities in Knowledge GraphsCode1
Secure Deep Graph Generation with Link Differential PrivacyCode1
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Benchmark Results

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