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 201225 of 1949 papers

TitleStatusHype
Automatic Relation-aware Graph Network ProliferationCode1
Boosting Graph Embedding on a Single GPUCode1
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding AggregationCode1
AutoRDF2GML: Facilitating RDF Integration in Graph Machine LearningCode1
CrossWalk: Fairness-enhanced Node Representation LearningCode1
CSGCL: Community-Strength-Enhanced Graph Contrastive LearningCode1
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph LearningCode1
DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity TypingCode1
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge GraphsCode1
Global Self-Attention as a Replacement for Graph ConvolutionCode1
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022Code1
Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base EmbeddingsCode1
Inductive Entity Representations from Text via Link PredictionCode1
Inductive Link Prediction for Nodes Having Only Attribute InformationCode1
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoningCode1
BiomedRAG: A Retrieval Augmented Large Language Model for BiomedicineCode1
Benchmarking Graph Neural Networks on Dynamic Link PredictionCode1
Demographic Aware Probabilistic Medical Knowledge Graph Embeddings of Electronic Medical RecordsCode1
An Open Challenge for Inductive Link Prediction on Knowledge GraphsCode1
Keep It Simple: Graph Autoencoders Without Graph Convolutional NetworksCode1
Argumentative Link Prediction using Residual Networks and Multi-Objective LearningCode1
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural NetworksCode1
Bipartite Graph Embedding via Mutual Information MaximizationCode1
BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph CompletionCode1
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge NetworksCode1
Show:102550
← PrevPage 9 of 78Next →

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