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Engineering and Technology

D-Index
42
Citations
15936
World Ranking
6357
National Ranking
1742

Overview

Patrick van der Smagt is affiliated with Volkswagen Group in the United States. Their research spans multiple fields within computer science and engineering, focusing extensively on artificial intelligence, robotics, and astrophysics. They have contributed significantly to topics such as reinforcement learning in robotics, generative adversarial networks, advanced vision and imaging, as well as studies related to gamma-ray bursts, supernovae, and broader stellar and galactic phenomena.

Their recent publications reflect a diverse range of interests and applications. Notable papers include:

  • Layerwise learning for quantum neural networks, 2021, Quantum Machine Intelligence
  • Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation, 2021, IEEE Transactions on Robotics
  • Learning to Fly via Deep Model-Based Reinforcement Learning, 2020, arXiv (Cornell University)
  • Dalek: A Deep Learning Emulator for TARDIS, 2021, The Astrophysical Journal Letters
  • Probabilistic Reconstruction of Type Ia Supernova SN 2002bo, 2021, The Astrophysical Journal Letters

They frequently collaborate with several researchers, including Nutan Chen, Wolfgang Kerzendorf, Maximilian Karl, Johannes Büchner, and C. Vogl.

The scientist's work appears regularly in publication venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • The Astrophysical Journal Letters
  • Computer Methods in Applied Mechanics and Engineering
  • The Astrophysical Journal

Patrick van der Smagt's main areas of study include:

  • Computer Science
  • Engineering

Within these, subfields they frequently investigate are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Astronomy and Astrophysics
  • Control and Systems Engineering
  • Biomedical Engineering

Key topics of their research include:

  • Gamma-ray bursts and supernovae
  • Reinforcement Learning in Robotics
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Vision and Imaging
  • Robot Manipulation and Learning
  • Robotics and Sensor-Based Localization
  • Stellar, planetary, and galactic studies

Best Publications

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Alexey Dosovitskiy;Philipp Fischery;Eddy Ilg;Philip Hausser

  • Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

    Leigh Robert Hochberg;Daniel Bacher;Beata Jarosiewicz;Beata Jarosiewicz;Nicolas Y. Masse

  • An introduction to Neural Networks

    Ben Kröse;Patrick van der Smagt

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Philipp Fischer;Alexey Dosovitskiy;Eddy Ilg;Philip Häusser

  • Surface EMG in advanced hand prosthetics

    Claudio Castellini;Patrick van der Smagt

  • Layerwise learning for quantum neural networks

    Andrea Skolik;Jarrod McClean;Masoud Mohseni;Patrick van der Smagt

  • Minimisation methods for training feedforward neural networks

    P. Patrick van der Smagt

  • Building the Ninapro database: A resource for the biorobotics community

    Manfredo Atzori;Arjan Gijsberts;Simone Heynen;Anne-Gabrielle Mittaz Hager

  • Learning EMG control of a robotic hand: towards active prostheses

    Unknown

  • Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.

    Maximilian Karl;Maximilian Soelch;Justin Bayer;Patrick van der Smagt

  • CNN-based Segmentation of Medical Imaging Data.

    Baris Kayalibay;Grady Jensen;Patrick van der Smagt

  • Neural network control of a pneumatic robot arm

    T. Hesselroth;K. Sarkar;P.P. van der Smagt;K. Schulten

  • Robots Driven by Compliant Actuators: Optimal Control Under Actuation Constraints

    David J. Braun;Florian Petit;Felix Huber;Sami Haddadin

  • Learning techniques in a dataglove based telemanipulation system for the DLR hand

    M. Fischer;P. van der Smagt;G. Hirzinger

  • Stable reinforcement learning with autoencoders for tactile and visual data

    Herke van Hoof;Nutan Chen;Maximilian Karl;Patrick van der Smagt

  • Two-stream RNN/CNN for action recognition in 3D videos

    Rui Zhao;Haider Ali;Patrick van der Smagt

  • Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform.

    Egidio Falotico;Lorenzo Vannucci;Alessandro Ambrosano;Ugo Albanese

  • EMG-based teleoperation and manipulation with the DLR LWR-III

    Jorn Vogel;Claudio Castellini;Patrick van der Smagt

  • Human hand modelling: kinematics, dynamics, applications

    Agneta Gustus;Georg Stillfried;Judith Visser;Henrik Jörntell

  • Antagonism for a Highly Anthropomorphic Hand-Arm System

    Markus Grebenstein;P. Patrick van der Smagt

  • Analysis and control of a rubbertuator arm

    P.P.P. van der Smagt;F.C.A. Groen;K.A.J. Schulten

  • Image Super-Resolution with Fast Approximate Convolutional Sparse Coding

    Christian Osendorfer;Hubert Soyer;Patrick van der Smagt

  • Sequential feature selection for classification

    Thomas Rückstieß;Christian Osendorfer;Patrick van der Smagt

Frequent Co-Authors

Claudio Castellini
Claudio Castellini University of Erlangen-Nuremberg
Sami Haddadin
Sami Haddadin Mohamed bin Zayed University of Artificial Intelligence
Jan Peters
Jan Peters Technical University of Darmstadt
John P. Donoghue
John P. Donoghue Brown University
Gerd Hirzinger
Gerd Hirzinger German Aerospace Center
Alois Knoll
Alois Knoll Technical University of Munich
Eduardo Ros
Eduardo Ros University of Granada
Leigh R. Hochberg
Leigh R. Hochberg Harvard University
Frans C. A. Groen
Frans C. A. Groen University of Amsterdam
Markus Grebenstein
Markus Grebenstein German Aerospace Center

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