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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–625 of 1949 papers

TitleStatusHype
Structural Explanations for Graph Neural Networks using HSIC—0
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning—0
Interaction Order Prediction for Temporal Graphs—0
PubGraph: A Large-Scale Scientific Knowledge Graph—0
Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph EmbeddingCode1
Neural Common Neighbor with Completion for Link PredictionCode1
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
Causal Lifting and Link Prediction—0
KG-Hub -- Building and Exchanging Biological Knowledge Graphs—0
Simplifying Subgraph Representation Learning for Scalable Link PredictionCode1
Adapting Neural Link Predictors for Data-Efficient Complex Query Answering—0
DBGDGM: Dynamic Brain Graph Deep Generative Model—0
Dual Box Embeddings for the Description Logic EL++Code0
Who Should I Engage with At What Time? A Missing Event Aware Temporal Graph Neural NetworkCode0
GIPA: A General Information Propagation Algorithm for Graph LearningCode1
Sem@K: Is my knowledge graph embedding model semantic-aware?Code1
There is No Big Brother or Small Brother: Knowledge Infusion in Language Models for Link Prediction and Question AnsweringCode0
IMKGA-SM: Interpretable Multimodal Knowledge Graph Answer Prediction via Sequence ModelingCode2
Analogical Inference Enhanced Knowledge Graph EmbeddingCode1
IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying ScaleCode0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs—0
Generative Graph Neural Networks for Link PredictionCode1
GANExplainer: GAN-based Graph Neural Networks Explainer—0
Customizing Knowledge Graph Embedding to Improve Clinical Study Recommendation—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