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Publications

Displaying results 31 to 40 of 676.
  1. Fabio Muratore; Michael Gienger; Jan Peters

    Assessing Transferability From Simulation to Reality for Reinforcement Learning

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 43, No. 4, Pages 1172-1183, IEEE, 2021.

  2. Riad Akrour; Asma Atamna; Jan Peters

    Convex optimization with an interpolation-based projection and its application to deep learning

    In: Machine Learning, Vol. 110, No. 8, Pages 2267-2289, Springer, 2021.

  3. Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters; Marcello Restelli

    Gaussian Approximation for Bias Reduction in Q-Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 277:1-277:51, JMLR, 2021.

  4. Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters

    MushroomRL: Simplifying Reinforcement Learning Research

    In: Journal of Machine Learning Research, Vol. 22, Pages 131:1-131:5, JMLR, 2021.

  5. Niyati Rawal; Dorothea Koert; Cigdem Turan; Kristian Kersting; Jan Peters; Ruth Stock-Homburg

    ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition

    In: Frontiers in Robotics and AI, Vol. 8, Pages 0-10, Frontiers, 2021.

  6. Boris Belousov; Hany Abdulsamad; Pascal Klink; Simone Parisi; Jan Peters

    Reinforcement learning algorithms: analysis and applications

    Springer, 2021.

  7. Bastian Wibranek; Yuxi Liu; Niklas Funk; Boris Belousov; Jan Peters; Oliver Tessmann

    Reinforcement learning for sequential assembly of SL-blocks-self-interlocking combinatorial design based on machine learning

    In: Vesna Stojaković; Bojan Tepavčević (Hrsg.). eCAADe 2021 - Towards a New, Configurable Architecture, Volume 1 - Proceedings. Education and Research …

  8. Thomas Röfer; Tim Laue; Nikolai Bahr; Jonah Jaeger; Jannes Knychalla; Thorben Lorenzen; Nele Matschull; Yannik Meinken; Lukas Malte Monnerjahn; Lukas Plecher; Philip Reichenberg

    B-Human Team Report and Code Release 2021

    2021.

  9. Patrick Trampert; Dmitri Rubinstein; Faysal Boughorbel; Christian Schlinkmann; Maria Luschkova; Philipp Slusallek; Tim Dahmen; Stefan Sandfeld

    Deep Neural Networks for Analysis of Microscopy Images—Synthetic Data Generation and Adaptive Sampling

    In: Paolo Olivero (Hrsg.). Crystals, Vol. 11, No. 258, Pages 1-13, MDPI, 3/2021.