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 1201–1250 of 1949 papers

TitleStatusHype
SPAN: Subgraph Prediction Attention Network for Dynamic Graphs—0
RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks—0
HopfE: Knowledge Graph Representation Learning using Inverse Hopf FibrationsCode0
Automatic Detection of COVID-19 Vaccine Misinformation with Graph Link PredictionCode0
Effective Model Integration Algorithm for Improving Link and Sign Prediction in Complex Networks—0
Learning Faithful Representations of Causal Graphs—0
OKGIT: Open Knowledge Graph Link Prediction with Implicit TypesCode0
Local2Global: Scaling global representation learning on graphs via local trainingCode0
Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning—0
Graph Representation Learning on Tissue-Specific Multi-Omics—0
ROD: Reception-aware Online Distillation for Sparse GraphsCode0
Data Considerations in Graph Representation Learning for Supply Chain Networks—0
Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021—0
PatentMiner: Patent Vacancy Mining via Context-enhanced and Knowledge-guided Graph Attention—0
Automated Graph Learning via Population Based Self-Tuning GCN—0
On Generalization of Graph Autoencoders with Adversarial TrainingCode0
Asymptotics of Network Embeddings Learned via SubsamplingCode0
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction—0
Trans4E: Link Prediction on Scholarly Knowledge Graphs—0
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective—0
Latent Space Model for Higher-order Networks and Generalized Tensor Decomposition—0
Convolutional Hypercomplex Embeddings for Link PredictionCode0
Leveraging Static Models for Link Prediction in Temporal Knowledge Graphs—0
KGRefiner: Knowledge Graph Refinement for Improving Accuracy of Translational Link Prediction Methods—0
OKGIT: Open Knowledge Graph Link Prediction with Implicit TypesCode0
Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction—0
Neural Concept Formation in Knowledge GraphsCode0
A Deep Latent Space Model for Graph Representation LearningCode0
ConvDySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention and Convolutional Neural NetworksCode0
Large-Scale Network Embedding in Apache Spark—0
Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path—0
CoANE: Modeling Context Co-occurrence for Attributed Network Embedding—0
Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs—0
Directed Graph Embeddings in Pseudo-Riemannian Manifolds—0
Node Classification Meets Link Prediction on Knowledge Graphs—0
Unified Interpretation of Softmax Cross-Entropy and Negative Sampling: With Case Study for Knowledge Graph EmbeddingCode0
Correcting Exposure Bias for Link RecommendationCode0
Inter-domain Multi-relational Link PredictionCode0
Learning Based Proximity Matrix Factorization for Node EmbeddingCode0
AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange—0
Multiple Kernel Representation Learning on NetworksCode0
Vertex-Centric Visual Programming for Graph Neural Networks—0
Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures—0
Network Estimation by Mixing: Adaptivity and More—0
Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism—0
A Systematic Investigation of KB-Text Embedding Alignment at ScaleCode0
Cross-Network Learning with Partially Aligned Graph Convolutional Networks—0
End-to-End Hierarchical Relation Extraction for Generic Form Understanding—0
Embedding Knowledge Graphs Attentive to Positional and Centrality QualitiesCode0
Motif Prediction with Graph Neural 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