2 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings
Yuqicheng Zhu, Nico Potyka, Bo Xiong +4
Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilisti…
Fantastic Data and How to Query Them
Trung-Kien Tran, Anh Le-Tuan, Manh Nguyen-Duc +2
It is commonly acknowledged that the availability of the huge amount of (training) data is one of the most important factors for many recent advances in Artificial Intelligence (AI…
Faithiful Embeddings for EL++ Knowledge Bases
Bo Xiong, Nico Potyka, Trung-Kien Tran +2
Recently, increasing efforts are put into learning continual representations for symbolic knowledge bases (KBs). However, these approaches either only embed the data-level knowledg…
Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs
Medina Andresel, Trung-Kien Tran, Csaba Domokos +2
Current methods for embedding-based query answering over incomplete Knowledge Graphs (KGs) only focus on inductive reasoning, i.e., predicting answers by learning patterns from the…