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 1051–1100 of 1949 papers

TitleStatusHype
MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering—0
Automating Neural Architecture Design without Search—0
SpaceE: Knowledge Graph Embedding by Relational Linear Transformation in the Entity Space—0
RNNCTPs: A Neural Symbolic Reasoning Method Using Dynamic Knowledge Partitioning Technology—0
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles—0
BSAL: A Framework of Bi-component Structure and Attribute Learning for Link PredictionCode0
A Hierarchical N-Gram Framework for Zero-Shot Link PredictionCode0
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph—0
A Hierarchical Block Distance Model for Ultra Low-Dimensional Graph RepresentationsCode0
Multi-view graph structure learning using subspace merging on Grassmann manifold—0
Synthetic Graph Generation to Benchmark Graph Learning—0
A Survey on Graph Representation Learning Methods—0
An unsupervised cluster-level based method for learning node representations of heterogeneous graphs in scientific papers—0
AdaGrid: Adaptive Grid Search for Link Prediction Training ObjectiveCode0
Revisiting Neighborhood-based Link Prediction for Collaborative Filtering—0
Augmenting Knowledge Graphs for Better Link PredictionCode0
Context-Dependent Anomaly Detection with Knowledge Graph Embedding Models—0
ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations—0
RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion—0
SimHawNet: A Modified Hawkes Process for Temporal Network SimulationCode0
Neural Theorem Provers Delineating Search Area Using RNN—0
LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings—0
Deep Partial Multiplex Network Embedding—0
Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks—0
HTGN-BTW: Heterogeneous Temporal Graph Network with Bi-Time-Window Training Strategy for Temporal Link Prediction—0
Improving the Level of Autism Discrimination through GraphRNN Link Prediction—0
Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion—0
CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs—0
STaR: Knowledge Graph Embedding by Scaling, Translation and Rotation—0
Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network—0
InterHT: Knowledge Graph Embeddings by Interaction between Head and Tail Entities—0
Obtaining Dyadic Fairness by Optimal TransportCode0
Bandit Sampling for Multiplex Networks—0
Link Prediction of Artificial Intelligence Concepts using Low Computational PowerCode0
Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning—0
From Discrimination to Generation: Knowledge Graph Completion with Generative TransformerCode0
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series—0
Collaborative filtering via heterogeneous neural networks—0
PPPNE: Personalized proximity preserved network embedding—0
Learning Representations of Entities and Relations—0
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification—0
Link Prediction with Contextualized Self-Supervision—0
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach—0
Fair Node Representation Learning via Adaptive Data Augmentation—0
Network-based link prediction of scientific concepts -- a Science4Cast competition entryCode0
SigGAN : Adversarial Model for Learning Signed Relationships in Networks—0
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections—0
Learning to Borrow– Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion—0
Combinatorial Scientific Discovery: Finding New Concept Combinations Beyond Link Prediction—0
Efficient layout-aware pretraining for multimodal form understanding—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