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 1426–1450 of 1949 papers

TitleStatusHype
GRADE: Graph Dynamic Embedding—0
Dual Graph Embedding for Object-Tag LinkPrediction on the Knowledge Graph—0
Are Hyperbolic Representations in Graphs Created Equal?—0
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing—0
Next Waves in Veridical Network Embedding—0
Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information—0
GraphOpt: Learning Optimization Models of Graph Formation—0
Pre-Trained Models for Heterogeneous Information Networks—0
Faster Graph Embeddings via CoarseningCode0
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs—0
Premise Selection in Natural Language Mathematical Texts—0
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear SubspacesCode0
Graph Clustering with Graph Neural Networks—0
Mobile Link Prediction: Automated Creation and Crowd-sourced Validation of Knowledge Graphs—0
Adversarial Learning for Debiasing Knowledge Graph Embeddings—0
A metric on directed graphs and Markov chains based on hitting probabilitiesCode0
Non-Parametric Graph Learning for Bayesian Graph Neural Networks—0
Spectral Evolution with Approximated Eigenvalue Trajectories for Link Prediction—0
Quantifying Challenges in the Application of Graph Representation Learning—0
Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks—0
Markov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic NetworksCode0
Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction—0
5* Knowledge Graph Embeddings with Projective Transformations—0
Graph Representation Learning Network via Adaptive SamplingCode0
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs—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