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 951–1000 of 1949 papers

TitleStatusHype
A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models—0
A Critical Examination of RESCAL for Completion of Knowledge Bases with Transitive Relations—0
A Novel Graph Transformer Framework for Gene Regulatory Network Inference—0
Deep Generative Models for Relational Data with Side Information—0
Node Level Graph Autoencoder: Unified Pretraining for Textual Graph Learning—0
Node Representation Learning for Directed Graphs—0
Node-Specific Space Selection via Localized Geometric Hyperbolicity in Graph Neural Networks—0
Nondiagonal Mixture of Dirichlet Network Distributions for Analyzing a Stock Ownership Network—0
Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Models—0
Non-Parametric Graph Learning for Bayesian Graph Neural Networks—0
Nonparametric Latent Feature Models for Link Prediction—0
Nonparametric Link Prediction in Dynamic Networks—0
Nonparametric Link Prediction in Large Scale Dynamic Networks—0
Nonparametric Multi-group Membership Model for Dynamic Networks—0
Nonparametric Relational Topic Models through Dependent Gamma Processes—0
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction—0
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks—0
NP^2L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks—0
NPGLM: A Non-Parametric Method for Temporal Link Prediction—0
Deep Hashing for Signed Social Network Embedding—0
Deep Learning in Mobile and Wireless Networking: A Survey—0
OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction—0
OFFER: A Motif Dimensional Framework for Network Representation Learning—0
DeepLink: A Novel Link Prediction Framework based on Deep Learning—0
On a Bernoulli Autoregression Framework for Link Discovery and Prediction—0
Deep Partial Multiplex Network Embedding—0
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections—0
Enhancing Cross-domain Link Prediction via Evolution Process Modeling—0
One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs—0
Hyperdimensional Representation Learning for Node Classification and Link Prediction—0
One-shot Learning for Temporal Knowledge Graphs—0
Deep Representation Learning for Social Network Analysis—0
On Large-scale Evaluation of Embedding Models for Knowledge Graph Completion—0
Online graph nets—0
Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information—0
On Masked Language Models for Contextual Link Prediction—0
On Multi-Relational Link Prediction with Bilinear Models—0
On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs—0
Deep Sparse Latent Feature Models for Knowledge Graph Completion—0
On the Equivalence of Holographic and Complex Embeddings for Link Prediction—0
On the ERM Principle with Networked Data—0
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks—0
DeepTrax: Embedding Graphs of Financial Transactions—0
On the Model Shrinkage Effect of Gamma Process Edge Partition Models—0
Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning—0
On the use of local structural properties for improving the efficiency of hierarchical community detection methods—0
On Understanding Knowledge Graph Representation—0
Interpreting Knowledge Graph Relation Representation from Word Embeddings—0
Degree-Based Random Walk Approach for Graph Embedding—0
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks—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