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Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models
  for Low-Dimensional Knowledge Graph Embeddings

Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models for Low-Dimensional Knowledge Graph Embeddings

27 March 2021
Kai Wang
Yu Liu
Dan Lin
Quan Z. Sheng
ArXivPDFHTML

Papers citing "Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models for Low-Dimensional Knowledge Graph Embeddings"

4 / 4 papers shown
Title
Knowledge Graph Embedding with 3D Compound Geometric Transformations
Knowledge Graph Embedding with 3D Compound Geometric Transformations
Xiou Ge
Yun Cheng Wang
Bin Wang
C.-C. Jay Kuo
34
6
0
01 Apr 2023
From Wide to Deep: Dimension Lifting Network for Parameter-efficient
  Knowledge Graph Embedding
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding
Borui Cai
Yong Xiang
Longxiang Gao
Di Wu
Heng Zhang
Jiongdao Jin
Tom H. Luan
34
1
0
22 Mar 2023
Ultrahyperbolic Knowledge Graph Embeddings
Ultrahyperbolic Knowledge Graph Embeddings
Bo Xiong
Shichao Zhu
M. Nayyeri
Chengjin Xu
Shirui Pan
Chuan Zhou
Steffen Staab
24
31
0
01 Jun 2022
Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional
  Knowledge Graph Embeddings
Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings
Kai Wang
Yu Liu
Quan.Z Sheng
25
18
0
03 Jan 2022
1