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 1376–1400 of 1949 papers

TitleStatusHype
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
A Framework for Large Scale Synthetic Graph Dataset Generation—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
A Dynamic Edge Exchangeable Model for Sparse Temporal Networks—0
NP^2L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks—0
NPGLM: A Non-Parametric Method for Temporal Link Prediction—0
Can we Soft Prompt LLMs for Graph Learning Tasks?—0
TPM: Transition Probability Matrix -- Graph Structural Feature based Embedding—0
Can Self Supervision Rejuvenate Similarity-Based Link Prediction?—0
A Community Detection and Graph Neural Network Based Link Prediction Approach for Scientific Literature—0
OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction—0
OFFER: A Motif Dimensional Framework for Network Representation Learning—0
Can Network Analysis Techniques help to Predict Design Dependencies? An Initial Study—0
Untargeted Adversarial Attack on Knowledge Graph Embeddings—0
The NOESIS Network-Oriented Exploration, Simulation, and Induction System—0
On a Bernoulli Autoregression Framework for Link Discovery and Prediction—0
Theoretical Rule-based Knowledge Graph Reasoning by Connectivity Dependency Discovery—0
Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks—0
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections—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