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Stephan Vogel

Stephan Vogel

D-Index & Metrics

Computer Science

D-Index
49
Citations
8124
World Ranking
5957
National Ranking
43

Overview

Stephan Vogel is affiliated with the University of Graz in Austria and focuses on research that bridges psychology, neuroscience, and mathematics. Their work primarily investigates cognitive and developmental aspects of mathematical skills, with additional emphasis on neuroscience, education, and cognitive function.

The main fields of study for Stephan Vogel include:

  • Psychology
  • Neuroscience
  • Mathematics

Their subfields of expertise cover:

  • Cognitive Neuroscience
  • Statistics and Probability
  • Developmental and Educational Psychology
  • Experimental and Cognitive Psychology
  • Education

Research topics are centered around:

  • Cognitive and developmental aspects of mathematical skills
  • Neuroscience, Education and Cognitive Function
  • Reading and Literacy Development
  • Mathematics Education and Teaching Techniques
  • Creativity in Education and Neuroscience
  • Education, Achievement, and Giftedness
  • Transcranial Magnetic Stimulation Studies

Stephan Vogel's publication record includes contributions to several frequent academic venues such as:

  • Neuropsychologia
  • Scientific Reports
  • Learning and Individual Differences
  • PLoS ONE
  • npj Science of Learning

Among recent papers, notable works by Stephan Vogel include:

  • Developmental brain dynamics of numerical and arithmetic abilities (2021) in npj Science of Learning

Frequent coauthors collaborating with Stephan Vogel are:

  • Roland H. Grabner
  • Michaela A. Meier
  • Clemens Brunner
  • Bert De Smedt
  • Jochen A. Mosbacher

Best Publications

  • HMM-based word alignment in statistical translation

    Stephan Vogel;Hermann Ney;Christoph Tillmann

  • Parallel Implementations of Word Alignment Tool

    Qin Gao;Stephan Vogel

  • Accelerated DP based search for statistical translation.

    Christoph Tillmann;Stephan Vogel;Hermann Ney;A. Zubiaga

  • Interpreting BLEU/NIST Scores: How Much Improvement do We Need to Have a Better System?

    Ying Zhang;Stephan Vogel;Alex Waibel

  • Active Learning and Crowd-Sourcing for Machine Translation

    Vamshi Ambati;Stephan Vogel;Jaime G. Carbonell

  • The CMU statistical machine translation system

    Stephan Vogel;Ying Zhang;Fei Huang;Alicia Tribble

  • Adaptation of the Translation Model for Statistical Machine Translation based on Information Retrieval

    Almut Silja Hildebrand;Matthias Eck;Stephan Vogel;Alex Waibel

  • Towards task recommendation in micro-task markets

    Vamshi Ambati;Stephan Vogel;Jaime Carbonell

  • Adaptive parallel sentences mining from web bilingual news collection

    Bing Zhao;S. Vogel

  • Algorithms for statistical translation of spoken language

    H. Ney;S. Niessen;F.J. Och;H. Sawaf

  • A DP-based Search Using Monotone Alignments in Statistical Translation

    Christoph Tillmann;Stephan Vogel;Hermann Ney;Alex Zubiaga

  • Word reordering in statistical machine translation with a POS-based distortion model.

    Kay Rottmann;Stephan Vogel

  • Language model adaptation for statistical machine translation with structured query models

    Bing Zhao;Matthias Eck;Stephan Vogel

  • Effective Phrase Translation Extraction from Alignment Models

    Ashish Venugopal;Stephan Vogel;Alex Waibel

  • A complete KALDI recipe for building Arabic speech recognition systems

    Ahmed Ali;Yifan Zhang;Patrick Cardinal;Najim Dahak

  • Mining Key Phrase Translations from Web Corpora

    Fei Huang;Ying Zhang;Stephan Vogel

  • On the ordinality of numbers: A review of neural and behavioral studies.

    I M Lyons;S E Vogel;D Ansari

  • An Efficient Phrase-to-Phrase Alignment Model for Arbitrarily Long Phrase and Large Corpora

    Ying Zhang;Stephan Vogel

  • Low cost Portability for statistical machine translation based on n-gram frequency and TF-IDF.

    Matthias Eck;Stephan Vogel;Alex Waibel

  • SMT decoder dissected: word reordering

    S. Vogel

  • Collaborative workflow for crowdsourcing translation

    Vamshi Ambati;Stephan Vogel;Jaime Carbonell

  • Automatic Extraction of Named Entity Translingual Equivalence Based on Multi-Feature Cost Minimization

    Fei Huang;Stephan Vogel;Alex Waibel

Frequent Co-Authors

Alex Waibel
Alex Waibel Carnegie Mellon University
Tanja Schultz
Tanja Schultz University of Bremen
Jaime G. Carbonell
Jaime G. Carbonell Carnegie Mellon University
Hermann Ney
Hermann Ney RWTH Aachen University
Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Alan W. Black
Alan W. Black Carnegie Mellon University
Jan Niehues
Jan Niehues Karlsruhe Institute of Technology
Noah A. Smith
Noah A. Smith University of Washington
Franz Josef Och
Franz Josef Och Google (United States)
Lori Levin
Lori Levin Carnegie Mellon University

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