graph embedding - Robuta Search

https://neo4j.com/blog/developer/enhancing-word-embedding-with-graph-neural-networks/

Enhancing Word Embedding with Graph Neural Networks

Combine word embeddings with graph neural networks using Neo4j. Enhance NLP models and extract context-rich language insights.

graph neural networks word embedding enhancing

https://aclanthology.org/I17-1088/

Course Concept Extraction in MOOCs via Embedding-Based Graph Propagation - ACL Anthology

Liangming Pan, Xiaochen Wang, Chengjiang Li, Juanzi Li, Jie Tang. Proceedings of the Eighth International Joint Conference on Natural Language Processing...

course concept extraction moocs via

https://openreview.net/forum?id=F3dOOE1tao&referrer=%5Bthe%20profile%20of%20Jiarong%20Pan%5D(%2Fprofile%3Fid%3D~Jiarong_Pan1)

Conformalized Answer Set Prediction for Knowledge Graph Embedding | OpenReview

Knowledge graph embeddings (KGE) apply machine learning methods on knowledge graphs (KGs) to provide non-classical reasoning capabilities based on similarities...

knowledge graph embedding answer set prediction openreview

https://aclanthology.org/2023.findings-acl.900/

Contrastive Learning with Generated Representations for Inductive Knowledge Graph Embedding - ACL...

Qian Li, Shafiq Joty, Daling Wang, Shi Feng, Yifei Zhang, Chengwei Qin. Findings of the Association for Computational Linguistics: ACL 2023. 2023.

knowledge graph embedding contrastive learning generated representations inductive

https://www.arxiv.org/abs/2312.16834

[2312.16834] Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding

Abstract page for arXiv paper 2312.16834: Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding

high dimensional graph embedding hierarchical aggregations multiplex

https://aclanthology.org/2020.textgraphs-1.1/

A survey of embedding models of entities and relationships for knowledge graph completion - ACL...

Dat Quoc Nguyen. Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs). 2020.

embedding models survey entities relationships

https://openreview.net/forum?id=4odAwBAhQ2&referrer=%5Bthe%20profile%20of%20Jiarong%20Pan%5D(%2Fprofile%3Fid%3D~Jiarong_Pan1)

Uncertainty Quantification of Knowledge Graph Embedding with Statistical Guarantees | OpenReview

Knowledge Graph Embedding (KGE) methods have been widely used in downstream tasks such as link prediction and question answering. However, a critical...

knowledge graph embedding uncertainty quantification statistical guarantees openreview

https://arxiv.org/abs/1509.05488

[1509.05488] TransG : A Generative Mixture Model for Knowledge Graph Embedding

Abstract page for arXiv paper 1509.05488: TransG : A Generative Mixture Model for Knowledge Graph Embedding

mixture model knowledge graph generative

https://www.arxiv.org/abs/2303.13284

[2303.13284] GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering

Abstract page for arXiv paper 2303.13284: GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering

graph embedding gett qa based transformer

https://deepai.org/publication/graph-embedding-with-shifted-inner-product-similarity-and-its-improved-approximation-capability

Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability |...

10/04/18 - We propose shifted inner-product similarity (SIPS), which is a novel yet very simple extension of the ordinary inner-product simil...

graph embedding inner product shifted similarity improved

https://www.ornl.gov/publication/augmenting-graph-convolution-distance-preserving-embedding-improved-learning

Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning... | ORNL

Graph convolution incorporates topological information of a graph into learning. Message passing corresponds to traversal of a local neighborhood in classical...

graph convolution distance preserving embedding