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 551575 of 1949 papers

TitleStatusHype
Scalable Deep Metric Learning on Attributed Graphs0
Hierarchical-Graph-Structured Edge Partition Models for Learning Evolving Community Structure0
MoCoKGC: Momentum Contrast Entity Encoding for Knowledge Graph Completion0
Enhancing Link Prediction with Fuzzy Graph Attention Networks and Dynamic Negative Sampling0
Shedding Light on Problems with Hyperbolic Graph Learning0
HeteroSample: Meta-path Guided Sampling for Heterogeneous Graph Representation Learning0
Discovering emergent connections in quantum physics research via dynamic word embeddingsCode0
YOSO: You-Only-Sample-Once via Compressed Sensing for Graph Neural Network Training0
Enhancing the Expressivity of Temporal Graph Networks through Source-Target IdentificationCode0
PageRank Bandits for Link PredictionCode0
G-SPARC: SPectral ARchitectures tackling the Cold-start problem in Graph learning0
An unified approach to link prediction in collaboration networksCode0
How to Bridge Spatial and Temporal Heterogeneity in Link Prediction? A Contrastive Method0
Capturing and Anticipating User Intents in Data Analytics via Knowledge Graphs0
Just Propagate: Unifying Matrix Factorization, Network Embedding, and LightGCN for Link Prediction0
Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production0
Geometric Feature Enhanced Knowledge Graph Embedding and Spatial Reasoning0
Can Self Supervision Rejuvenate Similarity-Based Link Prediction?0
Multi-frame Detection via Graph Neural Networks: A Link Prediction Approach0
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs0
Is Complex Query Answering Really Complex?0
CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype AssociationsCode0
Inference over Unseen Entities, Relations and Literals on Knowledge Graphs0
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter TuningCode0
When Graph Neural Networks Meet Dynamic Mode Decomposition0
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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