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 18761900 of 1949 papers

TitleStatusHype
Spring-Electrical Models For Link PredictionCode0
SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information EmbeddingCode0
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender SystemsCode0
Start from Zero: Triple Set Prediction for Automatic Knowledge Graph CompletionCode0
STransE: a novel embedding model of entities and relationships in knowledge basesCode0
Strong and Weak Random Walks on Signed NetworksCode0
Structural Alignment in Link PredictionCode0
Structural Deep Network EmbeddingCode0
Structure-Preference Enabled Graph Embedding Generation under Differential PrivacyCode0
Supra-Laplacian Encoding for Transformer on Dynamic GraphsCode0
Symbolic Hyperdimensional Vectors with Sparse Graph Convolutional Neural NetworksCode0
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation LearningCode0
TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation LearningCode0
Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient ModelingCode0
tBDFS: Temporal Graph Neural Network Leveraging DFSCode0
TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrixCode0
Temporal Graph Network Embedding with Causal Anonymous Walks RepresentationsCode0
Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation LearningCode0
Temporal Knowledge Base Completion: New Algorithms and Evaluation ProtocolsCode0
Temporal Link Prediction Using Graph Embedding DynamicsCode0
Temporal Link Prediction using Matrix and Tensor FactorizationsCode0
Temporal Network Representation Learning via Historical Neighborhoods AggregationCode0
Temporal receptive field in dynamic graph learning: A comprehensive analysisCode0
Dynamic Graph Convolutional Networks Using the Tensor M-ProductCode0
TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential DynamicsCode0
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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
8MEI (small)Hits@100.96Unverified
9ComplEx-N3 (reciprocal)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