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Link Prediction

222 papers with code · Graphs

Link prediction is a task to estimate the probability of links between nodes in a graph.

( Image credit: Inductive Representation Learning on Large Graphs )

Benchmarks

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Greatest papers with code

Benchmarking Graph Neural Networks

2 Mar 2020dmlc/dgl

Graph neural networks (GNNs) have become the standard toolkit for analyzing and learning from data on graphs.

GRAPH CLASSIFICATION GRAPH REGRESSION LINK PREDICTION NODE CLASSIFICATION

Graph Attention Networks

ICLR 2018 aymericdamien/TopDeepLearning

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.

DOCUMENT CLASSIFICATION GRAPH EMBEDDING GRAPH REGRESSION LINK PREDICTION NODE CLASSIFICATION SKELETON BASED ACTION RECOGNITION

PyTorch-BigGraph: A Large-scale Graph Embedding System

28 Mar 2019facebookresearch/PyTorch-BigGraph

Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks.

 Ranked #1 on Link Prediction on YouTube (Macro F1 metric)

GRAPH EMBEDDING GRAPH PARTITIONING LINK PREDICTION

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

20 Dec 2014facebookresearch/PyTorch-BigGraph

We consider learning representations of entities and relations in KBs using the neural-embedding approach.

LINK PREDICTION

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.

LINK PREDICTION NODE CLASSIFICATION REPRESENTATION LEARNING

Complex Embeddings for Simple Link Prediction

20 Jun 2016stellargraph/stellargraph

In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases.

LINK PREDICTION RELATIONAL REASONING

node2vec: Scalable Feature Learning for Networks

3 Jul 2016shenweichen/GraphEmbedding

Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks.

LINK PREDICTION MULTI-LABEL CLASSIFICATION NODE CLASSIFICATION REPRESENTATION LEARNING

Structural Deep Network Embedding

KDD 2016 shenweichen/GraphEmbedding

Therefore, how to find a method that is able to effectively capture the highly non-linear network structure and preserve the global and local structure is an open yet important problem.

GRAPH CLASSIFICATION LINK PREDICTION NETWORK EMBEDDING

LINE: Large-scale Information Network Embedding

12 Mar 2015shenweichen/GraphEmbedding

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.

GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

Knowledge Graph Completion via Complex Tensor Factorization

22 Feb 2017Accenture/AmpliGraph

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