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 1751–1800 of 1949 papers

TitleStatusHype
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction dataCode0
Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of NodesCode0
MPXGAT: An Attention based Deep Learning Model for Multiplex Graphs EmbeddingCode0
MSGCN: Multiplex Spatial Graph Convolution Network for Interlayer Link Weight PredictionCode0
mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network EmbeddingCode0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
Multi-Label Classification Using Link PredictionCode0
Multi-Label Zero-Shot Product Attribute-Value ExtractionCode0
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional NetworksCode0
Multiple Kernel Representation Learning on NetworksCode0
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph EmbeddingsCode0
Multi-relational Poincaré Graph EmbeddingsCode0
Multi-Task Graph AutoencodersCode0
Musical Voice Separation as Link Prediction: Modeling a Musical Perception Task as a Multi-Trajectory Tracking ProblemCode0
MUST: Multi-Scale Structural-Temporal Link Prediction Model for UAV Ad Hoc NetworksCode0
MyDigitalFootprint: an extensive context dataset for pervasive computing applications at the edgeCode0
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation LearningCode0
NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture SearchCode0
Natural-Parameter Networks: A Class of Probabilistic Neural NetworksCode0
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph EmbeddingCode0
Mutual Information Maximization in Graph Neural NetworksCode0
NestE: Modeling Nested Relational Structures for Knowledge Graph ReasoningCode0
NetGAN: Generating Graphs via Random WalksCode0
NetInfoF Framework: Measuring and Exploiting Network Usable InformationCode0
Network-based link prediction of scientific concepts -- a Science4Cast competition entryCode0
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link PredictionCode0
Network Representation Learning: Consolidation and Renewed BearingCode0
Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?Code0
Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network EmbeddingCode0
Neural Collaborative Filtering vs. Matrix Factorization RevisitedCode0
Neural Concept Formation in Knowledge GraphsCode0
Neural Graph Embedding Methods for Natural Language ProcessingCode0
Towards Neural Scaling Laws on GraphsCode0
Neural Subgraph Isomorphism CountingCode0
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph EmbeddingsCode0
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic GraphsCode0
NNKGC: Improving Knowledge Graph Completion with Node NeighborhoodsCode0
Node Attribute Completion in Knowledge Graphs with Multi-Relational PropagationCode0
Node Duplication Improves Cold-start Link PredictionCode0
Node Embedding over Temporal GraphsCode0
Node Embedding with Adaptive Similarities for Scalable Learning over GraphsCode0
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood PredictionCode0
Scalable and Efficient Temporal Graph Representation Learning via Forward Recent SamplingCode0
Normed Spaces for Graph EmbeddingCode0
Novel Node Category Detection Under Subpopulation ShiftCode0
Numerical Literals in Link Prediction: A Critical Examination of Models and DatasetsCode0
Obtaining Dyadic Fairness by Optimal TransportCode0
OKGIT: Open Knowledge Graph Link Prediction with Implicit TypesCode0
OKGIT: Open Knowledge Graph Link Prediction with Implicit TypesCode0
On Calibration of Graph Neural Networks for Node ClassificationCode0
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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