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researcher

Steffen Staab

University of Stuttgart, Germany, and University of Southampton, UK

14 papers hereh-index 9354 citations40 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4
  • last author10

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.LG4
  • cs.CV2
  • cs.CY1
  • cs.DB1
  • cs.IR1
affiliations
  • University of Stuttgart, Germany, and University of Southampton, UK
Homepage
same name
  • Steffen Staab — 36 papers, h 88
  • Steffen Staab — 35 papers, h 8
  • Steffen Staab — 8 papers, h 2
  • Steffen Staab — 5 papers, h 3
  • Steffen Staab — 5 papers, h 3
  • Steffen Staab — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedSCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks

61 citations · 133 across the 14 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2023★ 1 cited

Shrinking Embeddings for Hyper-Relational Knowledge Graphs

Bo Xiong, Mojtaba Nayyer, Shirui Pan +1

Link prediction on knowledge graphs (KGs) has been extensively studied on binary relational KGs, wherein each fact is represented by a triple. A significant amount of important kno…

cs.AI2023★ 3 cited

Geometric Relational Embeddings: A Survey

Bo Xiong, Mojtaba Nayyeri, Ming Jin +4

Geometric relational embeddings map relational data as geometric objects that combine vector information suitable for machine learning and structured/relational information for str…

cs.AI2023★ 27 cited

Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models

Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández +1

Predicting missing links between entities in a knowledge graph is a fundamental task to deal with the incompleteness of data on the Web. Knowledge graph embeddings map nodes into a…

cs.AI2022

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.