World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
18781
World Ranking
9021
National Ranking
447

Overview

Laurenz Wiskott is affiliated with Ruhr University Bochum in Germany. Their research spans multiple fields including Computer Science and Neuroscience, with a notable volume of publications in both areas.

The researcher has contributed significantly to subfields such as Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience, and various Computer Science Applications.

Main topics covered by their work include Reinforcement Learning in Robotics, Memory and Neural Mechanisms, Neural dynamics and brain function, Domain Adaptation and Few-Shot Learning, Neuroscience and Neuropharmacology Research, Explainable Artificial Intelligence (XAI), and Zebrafish Biomedical Research Applications.

Frequent co-authors in their collaborations include Sen Cheng, Raphael C. Engelhardt, Moritz Lange, Wolfgang Konen, and Robin Schiewer.

Their recent papers reflect a strong interest in memory, spatial learning, and computational neuroscience. Selected recent works include:

  • A Model of Semantic Completion in Generative Episodic Memory, 2022, Neural Computation
  • A map of spatial navigation for neuroscience, 2023, Neuroscience & Biobehavioral Reviews
  • Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach, 2021, Scientific Reports
  • A Tutorial on the Spectral Theory of Markov Chains, 2023, Neural Computation
  • Modeling the function of episodic memory in spatial learning, 2023, Frontiers in Psychology

Common venues for publication include arXiv (Cornell University), Neural Computation, bioRxiv (Cold Spring Harbor Laboratory), Neuroscience & Biobehavioral Reviews, and Scientific Reports, indicating engagement with both preprint platforms and peer-reviewed journals.

Best Publications

  • Face recognition by elastic bunch graph matching

    L. Wiskott;J.-M. Fellous;N. Kuiger;C. von der Malsburg

  • Face recognition by elastic bunch graph matching

    L. Wiskott;J.-M. Fellous;N. Kruger;C. von der Malsburg

  • Face recognition by elastic bunch graph matching

    Laurenz Wiskott;Jean-Marc Fellous;Norbert Krüger;Christoph von der Malsburg

  • Slow feature analysis: unsupervised learning of invariances

    Laurenz Wiskott;Terrence J. Sejnowski

  • Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?

    N. Kruger;P. Janssen;S. Kalkan;M. Lappe

  • Slow feature analysis yields a rich repertoire of complex cell properties.

    Pietro Berkes;Laurenz Wiskott

  • Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells

    Mathias Franzius;Henning Sprekeler;Laurenz Wiskott

  • Face Recognition and Gender determination

    Laurenz Wiskott;Jean-Marc Fellous;Norbert Krüger;Christoph von der Malsburg

  • Labeled bunch graphs for image analysis

    Laurenz Wiskott;Christoph von der Malsburg

  • Modular toolkit for Data Processing (MDP): a Python data processing framework

    Tiziano Zito;Niko Wilbert;Laurenz Wiskott;Pietro Berkes

  • Phantom faces for face analysis

    Laurenz Wiskott

  • Recognizing Faces by Dynamic Link Matching

    Laurenz Wiskott;Christoph von der Malsburg

  • CuBICA: independent component analysis by simultaneous third- and fourth-order cumulant diagonalization

    T. Blaschke;L. Wiskott

  • Reinforcement learning on slow features of high-dimensional input streams.

    Robert A. Legenstein;Niko Wilbert;Laurenz Wiskott

  • Slow feature analysis: a theoretical analysis of optimal free responses

    Laurenz Wiskott

  • Face recognition by dynamic link matching

    L. Wiskott

  • Slowness: an objective for spike-timing-dependent plasticity?

    Henning Sprekeler;Christian Michaelis;Laurenz Wiskott

  • Spatial representations of place cells in darkness are supported by path integration and border information

    Sijie Zhang;Fabian Schönfeld;Laurenz Wiskott;Denise Manahan-Vaughan

  • What Is the Relation Between Slow Feature Analysis and Independent Component Analysis

    Tobias Blaschke;Pietro Berkes;Laurenz Wiskott

  • A computational model for preplay in the hippocampus

    Amir Hossein Azizi;Laurenz Wiskott;Sen Cheng

  • From grids to places.

    Mathias Franzius;Roland Vollgraf;Laurenz Wiskott

Frequent Co-Authors

Christoph von der Malsburg
Christoph von der Malsburg Frankfurt Institute for Advanced Studies
Gerd Kempermann
Gerd Kempermann German Center for Neurodegenerative Diseases
Norbert Krüger
Norbert Krüger University of Southern Denmark
Jean-Marc Fellous
Jean-Marc Fellous University of Arizona
Robert Legenstein
Robert Legenstein Graz University of Technology
Denise Manahan-Vaughan
Denise Manahan-Vaughan Ruhr University Bochum
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Alessandro Treves
Alessandro Treves International School for Advanced Studies
Boris Gutkin
Boris Gutkin École Normale Supérieure
Simone Kühn
Simone Kühn Max Planck Institute for Human Development

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