World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
17435
World Ranking
6660
National Ranking
53

Overview

Christoph H. Lampert is affiliated with the Institute of Science and Technology Austria in Austria. Their primary field of study is Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Safety Research, and Computational Mechanics.

Their research spans multiple topics, particularly in areas such as Domain Adaptation and Few-Shot Learning, Adversarial Robustness in Machine Learning, Anomaly Detection Techniques and Applications, Machine Learning and Data Classification, Advanced Neural Network Applications, Privacy-Preserving Technologies in Data, and Advanced Vision and Imaging.

Christoph H. Lampert has an extensive publication record, with a significant number of papers published in various venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Journal of Spatial Information Science
  • 2021 IEEE International Conference on Big Data (Big Data)
  • 2022 26th International Conference on Pattern Recognition (ICPR)
  • Enlighten: Publications (The University of Glasgow)

Notable recent papers authored or co-authored by Christoph H. Lampert include:

  • "Towards Understanding Knowledge Distillation" (2021, arXiv (Cornell University))
  • "Continual Learning: Applications and the Road Forward" (2023, arXiv (Cornell University))
  • "Object-Centric Image Generation with Factored Depths, Locations, and Appearances" (2020, arXiv (Cornell University))
  • "Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis" (2021, 2021 IEEE International Conference on Big Data (Big Data))
  • "On the Sample Complexity of Adversarial Multi-Source PAC Learning" (2020, arXiv (Cornell University))

Frequent co-authors working with Christoph H. Lampert include:

  • Hossein Zakerinia
  • Bernd Prach
  • Paul Henderson
  • Nikola Konstantinov
  • Dan Alistarh

Best Publications

  • iCaRL: Incremental Classifier and Representation Learning

    Sylvestre-Alvise Rebuffi;Alexander Kolesnikov;Georg Sperl;Christoph H. Lampert

  • Learning to detect unseen object classes by between-class attribute transfer

    Christoph H Lampert;Hannes Nickisch;Stefan Harmeling

  • Attribute-Based Classification for Zero-Shot Visual Object Categorization

    Christoph H. Lampert;Hannes Nickisch;Stefan Harmeling

  • Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

    Yongqin Xian;Christoph H. Lampert;Bernt Schiele;Zeynep Akata

  • Beyond sliding windows: Object localization by efficient subwindow search

    C.H. Lampert;M.B. Blaschko;T. Hofmann

  • Seed, expand and constrain: Three principles for weakly-supervised image segmentation

    Alexander Kolesnikov;Christoph H. Lampert

  • Efficient Subwindow Search: A Branch and Bound Framework for Object Localization

    C.H. Lampert;M.B. Blaschko;T. Hofmann

  • Learning to Localize Objects with Structured Output Regression

    Matthew Blaschko;Christoph H Lampert

  • Structured Learning and Prediction in Computer Vision

    Sebastian Nowozin;Christoph H. Lampert

  • Correlational spectral clustering

    M.B. Blaschko;C.H. Lampert

  • Curriculum learning of multiple tasks

    Anastasia Pentina;Viktoriia Sharmanska;Christoph H. Lampert

  • Unsupervised Object Discovery: A Comparison

    Tinne Tuytelaars;Christoph H. Lampert;Matthew B. Blaschko;Wray Buntine

  • Learning to Rank Using Privileged Information

    Viktoriia Sharmanska;Novi Quadrianto;Christoph H. Lampert

  • Movement templates for learning of hitting and batting

    Jens Kober;Katharina Mulling;Oliver Kromer;Christoph H. Lampert

  • Distillation-Based Training for Multi-Exit Architectures

    Mary Phuong;Christoph Lampert

  • Document image dewarping using robust estimation of curled text lines

    A. Ulges;C.H. Lampert;T.M. Breuel

  • A PAC-Bayesian bound for Lifelong Learning

    Anastasia Pentina;Christoph Lampert

  • Kernel Methods in Computer Vision

    Christoph H. Lampert

  • Towards understanding knowledge distillation

    Mary Phuong;Christoph H. Lampert

  • Global connectivity potentials for random field models

    Sebastian Nowozin;Christoph H Lampert

  • Extrapolation and learning equations

    Georg Martius;Christoph H. Lampert

Frequent Co-Authors

Sebastian Nowozin
Sebastian Nowozin Microsoft (United States)
Thomas M. Breuel
Thomas M. Breuel Nvidia (United States)
Vittorio Ferrari
Vittorio Ferrari Google (United States)
Jan Peters
Jan Peters Technical University of Darmstadt
Vladimir Kolmogorov
Vladimir Kolmogorov Institute of Science and Technology Austria
Arthur Gretton
Arthur Gretton University College London
Andreas Bartels
Andreas Bartels Max Planck Society

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