Zoo Guide to Network Embedding
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Abstract (arXiv)
Networks have provided extremely successful models of data and complex systems. Yet, as combinatorial objects, networks do not have in general intrinsic coordinates and do not typically lie in an ambient space. The process of assigning an embedding space to a network has attracted lots of interest in the past few decades, and has been efficiently applied to fundamental problems in network inference, such as link prediction, node classification, and community detection. In this review, we provide a user-friendly guide to the network embedding literature and current trends in this field which will allow the reader to navigate through the complex landscape of methods and approaches emerging from the vibrant research activity on these subjects.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 105 of its 249 references that are in the map. First posted on arXiv 5 May 2023.
Builds on
105 of 249 references.
References · 105
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- 2017Graph Attention Networkscited by 8,854
- 2017Inductive Representation Learning on Large Graphscited by 6,284
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
- 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
- 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,085
- 2016node2vec: Scalable Feature Learning for Networkscited by 1,913
- 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
- 2014DeepWalk: Online Learning of Social Representationscited by 1,543
- 2016Variational Graph Auto-Encoderscited by 1,373
- 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,097
- 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 929
38 more
- 2016Complex Embeddings for Simple Link Predictioncited by 897
- 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 893
- 2018Representation Learning on Graphs with Jumping Knowledge Networkscited by 875
- 2018Hierarchical Graph Representation Learning with Differentiable Poolingcited by 786
- 2015Convolutional Networks on Graphs for Learning Molecular Fingerprintscited by 751
- 2019Heterogeneous Graph Attention Networkcited by 732
- 2017Poincar'e Embeddings for Learning Hierarchical Representationscited by 674
- 2015LINE: Large-scale Information Network Embeddingcited by 582
- 2018Hypergraph Neural Networkscited by 482
- 2017Representation Learning on Graphs: Methods and Applicationscited by 456
- 2019Hyperbolic Graph Convolutional Neural Networkscited by 400
- 2016Learning Convolutional Neural Networks for Graphscited by 314
- 2016Molecular Graph Convolutions: Moving Beyond Fingerprintscited by 238
- 2018Modeling polypharmacy side effects with graph convolutional networkscited by 237
- 2019Hypergraph Convolution and Hypergraph Attentioncited by 226
- 2021Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networkscited by 219
- 2021Weisfeiler and Lehman Go Cellular: CW Networkscited by 218
- 2017struc2vec: Learning Node Representations from Structural Identitycited by 214
- 2022Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNscited by 208
- 2018Representation Tradeoffs for Hyperbolic Embeddingscited by 204
- 2017Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2veccited by 197
- 2020Low-Dimensional Hyperbolic Knowledge Graph Embeddingscited by 195
- 2017Graph Embedding Techniques, Applications, and Performance: A Surveycited by 188
- 2020Machine Learning on Graphs: A Model and Comprehensive Taxonomycited by 156
- 2017A Survey on Network Embeddingcited by 142
- 2017Predicting multicellular function through multi-layer tissue networkscited by 138
- 2017Heterogeneous Information Network Embedding for Recommendationcited by 133
- 2016Discriminative Embeddings of Latent Variable Models for Structured Datacited by 130
- 2020Networks beyond pairwise interactions: structure and dynamicscited by 127
- 2017GraphGAN: Graph Representation Learning with Generative Adversarial Netscited by 121
- 2020Simplicial Neural Networkscited by 105
- 2021MagNet: A Neural Network for Directed Graphscited by 104
- 2017Network Representation Learning: A Surveycited by 101
- 2015PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networkscited by 96
- 2019Representation Learning for Attributed Multiplex Heterogeneous Networkcited by 91
- 2013Multilayer Networkscited by 86
- 2021Signal Processing on Higher-Order Networks: Livin' on the Edge ... and Beyondcited by 81
- 2021Graph Representation Learning in Biomedicinecited by 79
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