Link Prediction
Link prediction is a task to estimate the probability of links between nodes in a graph.
State-of-the-art leaderboards
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Subtasks
Greatest papers with code
PyTorch-BigGraph: A Large-scale Graph Embedding System
• facebookresearch/PyTorch-BigGraph
• 
Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks.
Embedding Entities and Relations for Learning and Inference in Knowledge Bases
• facebookresearch/PyTorch-BigGraph
•
We consider learning representations of entities and relations in KBs using the neural-embedding approach.
#7 best model for
Link Prediction
on WN18
Inductive Representation Learning on Large Graphs
NeurIPS 2017
• williamleif/GraphSAGE
• 
Low-dimensional embeddings of nodes in large graphs have proved extremely useful in a variety of prediction tasks, from content recommendation to identifying protein functions.
#10 best model for
Node Classification
on PubMed with Public Split: fixed 20 nodes per class
Graph Attention Networks
ICLR 2018
• PetarV-/GAT
•
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations.
#3 best model for
Document Classification
on Cora
DOCUMENT CLASSIFICATION GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION
Canonical Tensor Decomposition for Knowledge Base Completion
ICML 2018
• Accenture/AmpliGraph
•
The problem of Knowledge Base Completion can be framed as a 3rd-order binary tensor completion problem.
SOTA for Link Prediction on FB15k-237
Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.
KNOWLEDGE GRAPH COMPLETION LINK PREDICTION RELATIONAL REASONING
Complex Embeddings for Simple Link Prediction
In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases.
#6 best model for
Link Prediction
on WN18
Holographic Embeddings of Knowledge Graphs
Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs.
Translating Embeddings for Modeling Multi-relational Data
NeurIPS 2013
• Accenture/AmpliGraph
•
We consider the problem of embedding entities and relationships of multi-relational data in low-dimensional vector spaces.
LINE: Large-scale Information Network Embedding
This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.
#5 best model for
Node Classification
on Wikipedia
GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION