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Entity Embeddings

Entity Embeddings is a technique for applying deep learning to tabular data. It involves representing the categorical data of an information systems entity with multiple dimensions.

Papers

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Showing 11–20 of 151 papers

Title	Date	Tasks	Status	Hype	Score
Complex Temporal Question Answering on Knowledge Graphs	Sep 18, 2021	16kEntity Embeddings	CodeCode Available	1	5
InGram: Inductive Knowledge Graph Embedding via Relation Graphs	May 31, 2023	Entity EmbeddingsGraph Embedding	CodeCode Available	1	5
AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models	Jul 18, 2023	Entity AlignmentEntity Embeddings	CodeCode Available	1	5
MMEAD: MS MARCO Entity Annotations and Disambiguations	Sep 14, 2023	Entity Embeddings	CodeCode Available	1	5
BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs	Jun 6, 2023	AttributeEntity Embeddings	CodeCode Available	1	5
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation	Mar 17, 2022	Entity EmbeddingsFederated Learning	CodeCode Available	1	5
CoLAKE: Contextualized Language and Knowledge Embedding	Oct 1, 2020	Entity EmbeddingsKnowledge Graph Completion	CodeCode Available	1	5
Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding	Feb 3, 2023	Entity EmbeddingsGraph Embedding	CodeCode Available	1	5
ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities	May 20, 2022	Entity AlignmentEntity Embeddings	CodeCode Available	1	5
Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering	Oct 6, 2022	Entity EmbeddingsGraph Neural Network	CodeCode Available	1	5

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