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Computer Science

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38
Citations
8663
World Ranking
10037
National Ranking
504

Overview

Michael Wand is affiliated with Johannes Gutenberg University of Mainz in Germany. Their research primarily spans the fields of Computer Science and Engineering, with a strong focus on specialized subfields such as Artificial Intelligence, Materials Chemistry, Biomedical Engineering, Computer Vision and Pattern Recognition, and Molecular Biology.

The scientist's work covers a variety of major topics, including:

  • Machine Learning in Materials Science
  • Block Copolymer Self-Assembly
  • Advanced Text Analysis Techniques
  • Muscle activation and electromyography studies
  • Meteorological Phenomena and Simulations
  • Wind and Air Flow Studies
  • Fire effects on ecosystems

Michael Wand has contributed to numerous publications, with frequent appearances in venues such as arXiv (Cornell University), where they have published 8 works. Other publication venues include European Urology, Journal of NeuroEngineering and Rehabilitation, Chemical Science, and Journal of Computational Science.

Among their recent papers are:

  • Deep Learning Predicts Molecular Subtype of Muscle-invasive Bladder Cancer from Conventional Histopathological Slides, 2020, European Urology
  • User training for machine learning controlled upper limb prostheses: a serious game approach, 2021, Journal of NeuroEngineering and Rehabilitation
  • Reagent prediction with a molecular transformer improves reaction data quality, 2023, Chemical Science
  • Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability, 2021, arXiv (Cornell University)
  • End-to-End Prediction of Lightning Events from Geostationary Satellite Images, 2022, Preprints.org

The scientist frequently collaborates with other researchers including Jürgen Schmidhuber, Mikhail G. Andronov, Marc Stieffenhofer, Tristan Bereau, and Djork-Arné Clevert.

Best Publications

  • Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

    Chuan Li;Michael Wand

  • Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

    Chuan Li;Michael Wand

  • Pattern-aware Deformation Using Sliding Dockers

    Martin Bokeloh;Michael Wand;Vladlen Koltun;Hans-Peter Seidel

  • Symmetry in 3D Geometry: Extraction and Applications

    Niloy J. Mitra;Mark Pauly;Michael Wand;Duygu Ceylan

  • Interactive rendering of large volume data sets

    S. Guthe;M. Wand;J. Gonser;W. Strasser

  • Optimal HDR reconstruction with linear digital cameras

    Miguel Granados;Boris Ajdin;Michael Wand;Christian Theobalt

  • Structure-aware shape processing

    Niloy J. Mitra;Michael Wand;Hao Zhang;Daniel Cohen-Or

  • Lipreading with long short-term memory

    Michael Wand;Jan Koutnik;Jurgen Schmidhuber

  • Modeling coarticulation in EMG-based continuous speech recognition

    Tanja Schultz;Michael Wand

  • A connection between partial symmetry and inverse procedural modeling

    Martin Bokeloh;Michael Wand;Hans-Peter Seidel

  • The randomized z-buffer algorithm: interactive rendering of highly complex scenes

    Michael Wand;Matthias Fischer;Ingmar Peter;Friedhelm Meyer auf der Heide

  • Biosignal-Based Spoken Communication: A Survey

    Tanja Schultz;Michael Wand;Thomas Hueber;Dean J. Krusienski

  • Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data

    Michael Wand;Bart Adams;Maksim Ovsjanikov;Alexander Berner

  • Symmetry Detection Using Feature Lines

    Martin Bokeloh;Alexander Berner;Michael Wand;Michael Wand;Hans-Peter Seidel

  • Deep Learning Predicts Molecular Subtype of Muscle-invasive Bladder Cancer from Conventional Histopathological Slides.

    Ann-Christin Woerl;Markus Eckstein;Josephine Geiger;Daniel C. Wagner

  • Bayesian Point Cloud Reconstruction

    Philipp Jenke;Michael Wand;Martin Bokeloh;Andreas Schilling

  • Isometric registration of ambiguous and partial data

    Art Tevs;Martin Bokeloh;Michael Wand;Andreas Schilling

  • Reconstruction of deforming geometry from time-varying point clouds

    Michael Wand;Philipp Jenke;Qixing Huang;Martin Bokeloh

  • Animation cartography—intrinsic reconstruction of shape and motion

    Art Tevs;Alexander Berner;Michael Wand;Ivo Ihrke

  • A graph-based approach to symmetry detection

    A. Berner;M. Bokeloh;M. Wand;A. Schilling

  • Markerless Motion Capture with unsynchronized moving cameras

    Nils Hasler;Bodo Rosenhahn;Thorsten Thormahlen;Michael Wand

Frequent Co-Authors

Hans-Peter Seidel
Hans-Peter Seidel Max Planck Institute for Informatics
Tanja Schultz
Tanja Schultz University of Bremen
Jürgen Schmidhuber
Jürgen Schmidhuber King Abdullah University of Science and Technology
Niloy J. Mitra
Niloy J. Mitra University College London
Wolfgang Straßer
Wolfgang Straßer University of Tübingen
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Qixing Huang
Qixing Huang The University of Texas at Austin
Mark Pauly
Mark Pauly École Polytechnique Fédérale de Lausanne
Reinhard Klein
Reinhard Klein University of Bonn
Philipp Slusallek
Philipp Slusallek Saarland University

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