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 1151–1200 of 1949 papers

TitleStatusHype
A Hidden Challenge of Link Prediction: Which Pairs to Check?Code0
Adversarial Attack on Network Embeddings via Supervised Network PoisoningCode0
Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention—0
A Statistical Relational Approach to Learning Distance-based GCNs—0
A Unified Lottery Ticket Hypothesis for Graph Neural NetworksCode1
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional NetworksCode1
Memory-Associated Differential LearningCode0
Understanding Higher-order Structures in Evolving Graphs: A Simplicial Complex based Kernel Estimation Approach—0
Hyperedge Prediction using Tensor Eigenvalue DecompositionCode0
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs—0
LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign—0
Learning Graph Representations—0
Cleora: A Simple, Strong and Scalable Graph Embedding SchemeCode1
[Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base EmbeddingsCode1
Heterogeneous Graph based Deep Learning for Biomedical Network Link Prediction—0
Efficient Graph Deep Learning in TensorFlow with tf_geometricCode1
Calibrating and Improving Graph Contrastive LearningCode0
Identity-aware Graph Neural NetworksCode2
Knowledge Generation -- Variational Bayes on Knowledge GraphsCode0
NEMR: Network Embedding on Metric of Relation—0
GraphAttacker: A General Multi-Task GraphAttack FrameworkCode0
Membership Inference Attack on Graph Neural NetworksCode1
JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms—0
BiGCN: A Bi-directional Low-Pass Filtering Graph Neural Network—0
Disentangling homophily, community structure and triadic closure in networks—0
A Survey on Embedding Dynamic Graphs—0
Representation Learning of Reconstructed Graphs Using Random Walk Graph Convolutional Network—0
Incremental Learning on Growing Graphs—0
Graph Edit NetworksCode0
Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs—0
Graph Structural Aggregation for Explainable Learning—0
On Dyadic Fairness: Exploring and Mitigating Bias in Graph ConnectionsCode1
ColdExpand: Semi-Supervised Graph Learning in Cold Start—0
Higher-order Structure Prediction in Evolving Graph Simplicial Complexes—0
Polar Embedding—0
xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future LinksCode1
Adaptive Graph Diffusion NetworksCode1
Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction—0
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism—0
Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure—0
A Generalization of Transformer Networks to GraphsCode1
Relational Boosted BanditsCode0
Understanding graph embedding methods and their applications—0
Adversarial Permutation Guided Node Representations for Link PredictionCode0
Pair-view Unsupervised Graph Representation Learning—0
Bipartite Graph Embedding via Mutual Information MaximizationCode1
Explainable Link Prediction for Privacy-Preserving Contact Tracing—0
Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphsCode1
Improving Relation Extraction by Leveraging Knowledge Graph Link PredictionCode0
PPKE: Knowledge Representation Learning by Path-based Pre-training—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