mlsanityData to 7 Oct 2026

Geometric Relational Embeddings: A Survey

arXiv 2304.11949 ↗First posted 24 Apr 2023cs.AIcited by 8

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Abstract (arXiv)

Geometric relational embeddings map relational data as geometric objects that combine vector information suitable for machine learning and structured/relational information for structured/relational reasoning, typically in low dimensions. Their preservation of relational structures and their appealing properties and interpretability have led to their uptake for tasks such as knowledge graph completion, ontology and hierarchy reasoning, logical query answering, and hierarchical multi-label classification. We survey methods that underly geometric relational embeddings and categorize them based on (i) the embedding geometries that are used to represent the data; and (ii) the relational reasoning tasks that they aim to improve. We identify the desired properties (i.e., inductive biases) of each kind of embedding and discuss some potential future work.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 34 of its 66 references that are in the map. First posted on arXiv 24 Apr 2023.

Builds on

34 of 66 references.

References · 34

  1. 2020Low-Dimensional Hyperbolic Knowledge Graph Embeddingscited by 195
  2. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 169
  3. 2018Hyperbolic Entailment Cones for Learning Hierarchical Embeddingscited by 160
  4. 2018Poincar'e GloVe: Hyperbolic Word Embeddingscited by 155
  5. 2020Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphscited by 128
  6. 2015Order-Embeddings of Images and Languagecited by 112
  7. 2021Fully Hyperbolic Neural Networkscited by 107
  8. 2020BoxE: A Box Embedding Model for Knowledge Base Completioncited by 105
  9. 2014Word Representations via Gaussian Embeddingcited by 96
  10. 2021ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 78
  11. 2020Coherent Hierarchical Multi-Label Classification Networkscited by 65
  12. 2018Probabilistic Embedding of Knowledge Graphs with Box Lattice Measurescited by 64
22 more
  1. 2019EL Embeddings: Geometric construction of models for the Description Logic EL ++cited by 48
  2. 2020Hierarchical Image Classification using Entailment Cone Embeddingscited by 46
  3. 2021Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Conescited by 38
  4. 2021Modeling Fine-Grained Entity Types with Box Embeddingscited by 36
  5. 2020Improving Local Identifiability in Probabilistic Box Embeddingscited by 35
  6. 2020Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphscited by 35
  7. 2020Knowledge Association with Hyperbolic Knowledge Graph Embeddingscited by 31
  8. 2019Hyperbolic Interaction Model For Hierarchical Multi-Label Classificationcited by 30
  9. 2015TransG : A Generative Mixture Model for Knowledge Graph Embeddingcited by 28
  10. 2021Probabilistic Entity Representation Model for Reasoning over Knowledge Graphscited by 28
  11. 2022Faithiful Embeddings for EL++ Knowledge Basescited by 25
  12. 2021Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoningcited by 22
  13. 2019Hyperbolic Disk Embeddings for Directed Acyclic Graphscited by 21
  14. 2022GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphscited by 21
  15. 2022Ultrahyperbolic Knowledge Graph Embeddingscited by 20
  16. 20205* Knowledge Graph Embeddings with Projective Transformationscited by 19
  17. 2022Geometry Interaction Knowledge Graph Embeddingscited by 18
  18. 2022Description Logic EL++ Embeddings with Intersectional Closurecited by 15
  19. 2021Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvaturescited by 12
  20. 2022ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completioncited by 12
  21. 2022Dual-Geometric Space Embedding Model for Two-View Knowledge Graphscited by 12
  22. 2022A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learningcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 2; 2025: 0; 2026: 2.

8 papers.

  1. 2023Hyperbolic Representation Learning: Revisiting and Advancingcited by 21
  2. 2024Emergent Visual-Semantic Hierarchies in Image-Text Representationscited by 19
  3. 2023Shrinking Embeddings for Hyper-Relational Knowledge Graphscited by 12
  4. 2024Ontology Embedding: A Survey of Methods, Applications and Resourcescited by 12
  5. 2026NGDB-Zoo: Towards Efficient and Scalable Neural Graph Databases Trainingcited by 2
  6. 2023Leveraging Optimal Transport via Projections on Subspaces for Machine Learning Applicationscited by 1
  7. 2023Towards Consistent Language Models Using Declarative Constraintscited by 1
  8. 2026Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddingscited by 1