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Honda (Germany)

Germany

41 papers here510 citations across 41
fields
  • cs.RO14
  • cs.AI8
  • cs.HC4
  • eess.SY4
  • cs.LG3
  • quant-ph3
  • cs.CE2
  • cs.CV1
ROR 022c1xk47OpenAlex

affiliations via OpenAlex

output
20192026
most citedReal-World Anomaly Detection by using Digital Twin Systems and Weakly-Supervised Learning

176 citations

researchers with a paper here
  • Benedict Flade8 · h 7
  • J. Eggert8 · h 25
  • Tim Puphal7 · h 7
  • Malte Probst6 · h 9
  • Sebastian Schmitt4 profiles6 · h 16
  • Daniel Tanneberg4 · h 10
  • Simon Kohaut4 · h 4
  • Chao Wang2 profiles3 · h 5
  • D. Dhami3 · h 16
  • H. Wersing2 profiles3 · h 28
  • Jens Engel3 · h 5
  • Julian Eggert3 · h 4
collaborating institutions
  • Technische Universität DarmstadtDE10 papers
  • Honda (Japan)JP7 papers
  • Bielefeld UniversityDE3 papers
  • Eindhoven University of TechnologyNL3 papers
  • German Research Centre for Artificial IntelligenceDE2 papers
  • Hess (United States)US2 papers
  • Honda (United States)US2 papers
  • Institut des Sciences Cognitives Marc JeannerodFR2 papers
  • Nanyang Technological UniversitySG2 papers
  • Centrum Wiskunde & InformaticaNL1 paper
  • Cornell UniversityUS1 paper
  • Leiden UniversityNL1 paper
Showing 2026Show all

1 paper · 1 filter

quant-ph2026

Machine learning with minimal use of quantum computers: Provable advantages in Learning Under Quantum Privileged Information (LUQPI)

Vasily Bokov, Lisa Kohl, Sebastian Schmitt +1

Quantum machine learning (QML) is often listed as a promising candidate for useful applications of quantum computers, in part due to numerous proofs of possible quantum advantages.…

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