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

Showing 15261550 of 1949 papers

TitleStatusHype
Bandit Sampling for Multiplex Networks0
Adaptive Pseudo-Siamese Policy Network for Temporal Knowledge Prediction0
Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks0
Balancing Augmentation with Edge-Utility Filter for Signed GNNs0
Random Walks: A Review of Algorithms and Applications0
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion0
RCoCo: Contrastive Collective Link Prediction across Multiplex Network in Riemannian Space0
Towards Generating Explanations for ASP-Based Link Analysis using Declarative Program Transformations0
Towards Learning Cross-Modal Perception-Trace Models0
Reading The Web with Learned Syntactic-Semantic Inference Rules0
Auxiliary learning induced graph convolutional networks0
AutoWeird: Weird Translational Scoring Function Identified by Random Search0
Automating psychological hypothesis generation with AI: when large language models meet causal graph0
Automating Neural Architecture Design without Search0
Automated Graph Learning via Population Based Self-Tuning GCN0
Reconstructing commuters network using machine learning and urban indicators0
RECS: Robust Graph Embedding Using Connection Subgraphs0
Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling0
Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs0
Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning0
Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph0
Dynamic Graph Representation Learning via Edge Temporal States Modeling and Structure-reinforced Transformer0
Redefining Developer Assistance: Through Large Language Models in Software Ecosystem0
Towards Probabilistic Generative Models Harnessing Graph Neural Networks for Disease-Gene Prediction0
Refined Edge Usage of Graph Neural Networks for Edge Prediction0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoKGEHits@100.56Unverified
2CP-N3-RPHits@100.55Unverified
3DistMult (after variational EM)Hits@100.55Unverified
4KG-R3Hits@100.54Unverified
5LASSHits@100.53Unverified
6MDE_advHits@100.53Unverified
7GFA-NNHits@100.52Unverified
8KGRefinerHits@100.49Unverified
9ComplEx NSCachingHits@100.48Unverified
10LogicENNHits@100.47Unverified
#ModelMetricClaimedVerifiedStatus
1MoCoKGCHits@100.88Unverified
2KERMITHits@100.83Unverified
3MoCoSAHits@100.82Unverified
4SimKGCIB(+PB+SN)Hits@100.82Unverified
5C-LMKE(bert-base)Hits@100.79Unverified
6LASSHits@100.79Unverified
7LP-BERTHits@100.75Unverified
8KGLMHits@100.74Unverified
9StAR(Self-Adp)Hits@100.71Unverified
10PALTHits@100.69Unverified
#ModelMetricClaimedVerifiedStatus
1OpenKE (han2018openke)training time (s)11Unverified
2LibKGE (ruffinelli2020you)training time (s)10Unverified
3GraphVite (zhu2019graphvite)training time (s)6Unverified
4Inverse ModelHits@100.96Unverified
5QuatDEHits@100.96Unverified
6LineaREHits@100.96Unverified
7AutoKGEHits@100.96Unverified
8MEI (small)Hits@100.96Unverified
9ComplEx-N3 (reciprocal)Hits@100.96Unverified
10RotatEHits@100.96Unverified
#ModelMetricClaimedVerifiedStatus
1OPTransEHits@100.9Unverified
2AutoKGEMRR0.86Unverified
3ComplEx-N3 (reciprocal)MRR0.86Unverified
4LineaREMRR0.84Unverified
5DistMult (after variational EM)MRR0.84Unverified
6QuatEMRR0.83Unverified
7SEEKMRR0.83Unverified
8MEI-BTDMRR0.81Unverified
9MEI (small)MRR0.8Unverified
10pRotatEMRR0.8Unverified