Knowledge Graph Embeddings

71 papers with code • 0 benchmarks • 2 datasets

This task has no description! Would you like to contribute one?


Use these libraries to find Knowledge Graph Embeddings models and implementations
2 papers

Most implemented papers

Convolutional 2D Knowledge Graph Embeddings

TimDettmers/ConvE 5 Jul 2017

In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction


HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

cai-lw/KBGAN NAACL 2018

This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.

Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text

YueLiu/NeuralTripleTranslation 4 Jul 2018

Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

tensorflow/neural-structured-learning ACL 2020

However, existing hyperbolic embedding methods do not account for the rich logical patterns in KGs.

Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

niva-knowledge-graph/kgs_and_effect_prediction_2020 8 Dec 2021

Furthermore, we have implemented a fine-tuning architecture that adapts the knowledge graph embeddings to the effect prediction task and leads to better performance.

Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

muhaochen/MTransE 12 Nov 2016

Many recent works have demonstrated the benefits of knowledge graph embeddings in completing monolingual knowledge graphs.

Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings

worksheets/0xc757f29f ACL 2017

To model both structured knowledge and unstructured language, we propose a neural model with dynamic knowledge graph embeddings that evolve as the dialogue progresses.

DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning

xwhan/DeepPath EMNLP 2017

We study the problem of learning to reason in large scale knowledge graphs (KGs).