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 1501–1550 of 1949 papers

TitleStatusHype
Convolutional Hypercomplex Embeddings for Link PredictionCode0
Cooperative Network Learning for Large-Scale and Decentralized GraphsCode0
Correcting Exposure Bias for Link RecommendationCode0
Cross-Network Social User Embedding with Hybrid Differential Privacy GuaranteesCode0
Cross-View Graph Consistency Learning for Invariant Graph RepresentationsCode0
CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype AssociationsCode0
DeBayes: a Bayesian Method for Debiasing Network EmbeddingsCode0
Decompressing Knowledge Graph Representations for Link PredictionCode0
Deepened Graph Auto-Encoders Help Stabilize and Enhance Link PredictionCode0
DeepFork: Supervised Prediction of Information Diffusion in GitHubCode0
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via RankingCode0
Deep Generative Models for Subgraph PredictionCode0
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional NetworksCode0
Deep Insights into Noisy Pseudo Labeling on Graph DataCode0
DeepNC: Deep Generative Network CompletionCode0
Demystifying Distributed Training of Graph Neural Networks for Link PredictionCode0
DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic HierarchyCode0
Derivation of Back-propagation for Graph Convolutional Networks using Matrix Calculus and its Application to Explainable Artificial IntelligenceCode0
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measuresCode0
Development of a Knowledge Graph Embeddings Model for PainCode0
Differentiating Concepts and Instances for Knowledge Graph EmbeddingCode0
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter TuningCode0
DINE: Dimensional Interpretability of Node EmbeddingsCode0
Discovering emergent connections in quantum physics research via dynamic word embeddingsCode0
Discriminative Predicate Path Mining for Fact Checking in Knowledge GraphsCode0
Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional RotationCode0
Distill2Vec: Dynamic Graph Representation Learning with Knowledge DistillationCode0
Distributed Graph Embedding with Information-Oriented Random WalksCode0
Enhancing Dense Retrievers' Robustness with Group-level ReweightingCode0
Do Similar Entities have Similar Embeddings?Code0
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document DeduplicationCode0
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
Dr-COVID: Graph Neural Networks for SARS-CoV-2 Drug RepurposingCode0
DRUM: End-To-End Differentiable Rule Mining On Knowledge GraphsCode0
Duality of Link Prediction and Entailment Graph InductionCode0
DyCSC: Modeling the Evolutionary Process of Dynamic Networks Based on Cluster StructureCode0
DyG2Vec: Efficient Representation Learning for Dynamic GraphsCode0
DynamicGEM: A Library for Dynamic Graph Embedding MethodsCode0
Dynamic Graph Representation Learning via Self-Attention NetworksCode0
Dynamic Network Embedding via Incremental Skip-gram with Negative SamplingCode0
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation LearningCode0
Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking TechniqueCode0
DyRep: Learning Representations over Dynamic GraphsCode0
Edge Classification on Graphs: New Directions in Topological ImbalanceCode0
Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning ModelCode0
Efficient and Privacy-Preserved Link Prediction via Condensed GraphsCode0
Efficient Link Prediction via GNN Layers Induced by Negative SamplingCode0
Efficient Neural Common Neighbor for Temporal Graph Link PredictionCode0
Efficient Parallel Translating Embedding For Knowledge GraphsCode0
EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming EventsCode0
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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
8ComplEx-N3 (reciprocal)Hits@100.96—Unverified
9MEI (small)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