48 citations · 73 across the 4 of their papers we have counts for
9 papers
Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs
Chengjin Xu, Fenglong Su, Jens Lehmann
Entity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information…
Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion
Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen +1
Recent years, Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a Knowledge Graph (KG) into a g…
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph Embeddings
Chengjin Xu, Mojtaba Nayyeri, Sahar Vahdati +1
Among the top approaches of recent years, link prediction using knowledge graph embedding (KGE) models has gained significant attention for knowledge graph completion. Various embe…
TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation
Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury +2
In the last few years, there has been a surge of interest in learning representations of entitiesand relations in knowledge graph (KG). However, the recent availability of temporal…
Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations
Mojtaba Nayyeri, Chengjin Xu, Jens Lehmann +1
Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a knowledge graph into a geometric space (usu…
Knowledge Graph Embeddings in Geometric Algebras
Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen +1
Knowledge graph (KG) embedding aims at embedding entities and relations in a KG into a lowdimensional latent representation space. Existing KG embedding approaches model entities a…