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
A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?—0
Hyperbolic Graph Convolutional Neural NetworksCode1
Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets—0
Network2Vec Learning Node Representation Based on Space Mapping in Networks—0
Decoupling feature propagation from the design of graph auto-encoders—0
Towards Learning Cross-Modal Perception-Trace Models—0
DeepFork: Supervised Prediction of Information Diffusion in GitHubCode0
Tutorial on NLP-Inspired Network Embedding—0
Dynamic Graph Convolutional Networks Using the Tensor M-ProductCode0
Efficiently Embedding Dynamic Knowledge Graphs—0
Link Prediction via Graph Attention Network—0
Commonsense Knowledge Base Completion with Structural and Semantic ContextCode0
Rethinking Kernel Methods for Node Representation Learning on GraphsCode0
Dynamic Embedding on Textual Networks via a Gaussian ProcessCode0
GENN: Predicting Correlated Drug-drug Interactions with Graph Energy Neural Networks—0
Dynamic Joint Variational Graph Autoencoders—0
Learning Robust Representations with Graph Denoising Policy Network—0
Keep It Simple: Graph Autoencoders Without Graph Convolutional NetworksCode1
TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction—0
On the Equivalence between Positional Node Embeddings and Structural Graph RepresentationsCode0
Representation Learning with Ordered Relation Paths for Knowledge Graph CompletionCode0
Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph—0
Projected Canonical Decomposition for Knowledge Base Completion—0
On Understanding Knowledge Graph Representation—0
Interpreting Knowledge Graph Relation Representation from Word Embeddings—0
Learning Temporal Attention in Dynamic Graphs with Bilinear InteractionsCode0
Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding SpaceCode1
Stacking Models for Nearly Optimal Link Prediction in Complex NetworksCode1
Combination of Unified Embedding Model and Observed Features for Knowledge Graph Completion—0
Towards Generating Explanations for ASP-Based Link Analysis using Declarative Program Transformations—0
Kernel Node EmbeddingsCode0
KG-BERT: BERT for Knowledge Graph CompletionCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
Adversarial Robustness of Similarity-Based Link Prediction—0
A Method to Learn Embedding of a Probabilistic Medical Knowledge Graph: Algorithm Development—0
Adversarial Training Methods for Network EmbeddingCode1
Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot RelationsCode1
Initialization for Network Embedding: A Graph Partition Approach—0
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific NetworksCode0
Variational Graph Recurrent Neural NetworksCode1
Hyper-Path-Based Representation Learning for Hyper-NetworksCode0
Power Efficient Discontinuous Reception in THz and mmWave Wireless Systems—0
motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks—0
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding—0
AHINE: Adaptive Heterogeneous Information Network Embedding—0
LogicENN: A Neural Based Knowledge Graphs Embedding Model with Logical Rules—0
Benchmarks for Graph Embedding EvaluationCode0
HONEM: Learning Embedding for Higher Order Networks—0
HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion—0
RWR-GAE: Random Walk Regularization for Graph Auto EncodersCode0
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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