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 576–600 of 1949 papers

TitleStatusHype
Deep Partial Multiplex Network Embedding—0
Automated Graph Learning via Population Based Self-Tuning GCN—0
DeepLink: A Novel Link Prediction Framework based on Deep Learning—0
Neural graph embeddings as explicit low-rank matrix factorization for link prediction—0
Graph Embedding with Hierarchical Attentive Membership—0
Graphfool: Targeted Label Adversarial Attack on Graph Embedding—0
Deep Learning in Mobile and Wireless Networking: A Survey—0
Deep Hashing for Signed Social Network Embedding—0
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism—0
Graph Convolutional Gaussian Processes For Link Prediction—0
Relation Embedding with Dihedral Group in Knowledge Graph—0
Deep Generative Models for Relational Data with Side Information—0
Graph Collaborative Reasoning—0
Class-Balanced and Reinforced Active Learning on Graphs—0
Graph Clustering with Graph Neural Networks—0
Graph Contrastive Learning on Multi-label Classification for Recommendations—0
Graph Distance Neural Networks for Predicting Multiple Drug Interactions—0
AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding—0
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series—0
AceKG: A Large-scale Knowledge Graph for Academic Data Mining—0
Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood—0
A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation and Extrapolation—0
Graph-based Generalization Bounds for Learning Binary Relations—0
Deep Amortized Relational Model with Group-Wise Hierarchical Generative Process—0
Decoupling feature propagation from the design of graph auto-encoders—0
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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