PUB - Publikationen an der Universität Bielefeld

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• [12]
  

  2021 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2960159

  Moringen, A., Fleer, S., & Ritter, H. (2021). Meta-learning Haptic Exploration of Simple 3D Objects. 2021 IEEE World Haptics Conference Piscataway, NJ: IEEE.

  PUB | PDF
   
• [11]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2949926

  Mohanty, S. P., Czakon, J., Kaczmarek, K. A., Pyskir, A., Tarasiewicz, P., Kunwar, S., Rohrbach, J., et al. (2020). Deep Learning for Understanding Satellite Imagery: An Experimental Survey. Frontiers in Artificial Intelligence, 3, 534696. https://doi.org/10.3389/frai.2020.534696

  PUB | PDF | DOI | WoS | PubMed | Europe PMC
   
• [10]
  

  2020 | Bielefelder E-Dissertation | PUB-ID: 2949123

  Fleer, S. (2020). Scaffolding for learning from reinforcement: Improving interaction learning. Bielefeld: Universität Bielefeld. doi:10.4119/unibi/2949123

  PUB | Dateien verfügbar | DOI
   
• [9]
  

  2020 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2943876

  Moringen, A., Fleer, S., Walck, G., & Ritter, H. (2020). Attention-based Robot Learning of Haptic Interaction. In I. Nisky, J. Hartcher-O’Brien, M. Wiertlewski, & J. Smeets (Eds.), Lecture Notes in Computer Science: Vol. 12272. Haptics: Science, Technology, Applications. 12th International Conference, EuroHaptics 2020, Leiden, The Netherlands, September 6–9, 2020, Proceedings (pp. 462-470). Cham: Springer. doi:10.1007/978-3-030-58147-3_51

  PUB | PDF | DOI | Download (ext.)
   
• [8]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939850

  Fleer, S., Moringen, A., Klatzky, R. L., & Ritter, H. (2020). Learning efficient haptic shape exploration with a rigid tactile sensor array. PLOS ONE, 15(1), e0226880. doi:10.1371/journal.pone.0226880

  PUB | PDF | DOI | WoS | PubMed | Europe PMC | arXiv
   
• [7]
  

  2019 | Datenpublikation | PUB-ID: 2934182

  Fleer, S. (2019). Supplementary Material - Solving a tool-based interaction task using deep reinforcement learning with visual attention. Bielefeld University. doi:10.4119/unibi/2934182

  PUB | Dateien verfügbar | DOI
   
• [6]
  

  2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2935994

  Fleer, S., & Ritter, H. (2019). Solving a Tool-Based Interaction Task Using Deep Reinforcement Learning with Visual Attention. Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization. WSOM 2019, Advances in Intelligent Systems and Computing , 976, 231-240. Cham: Springer. doi:10.1007/978-3-030-19642-4_23

  PUB | DOI | Download (ext.)
   
• [5]
  

  2019 | Datenpublikation | PUB-ID: 2936475

  Fleer, S., Moringen, A., Klatzky, R. L., & Ritter, H. (2019). Supplementary Material - Learning efficient haptic shape exploration with a rigid tactile sensor array. Bielefeld University. doi:10.4119/unibi/2936475

  PUB | Dateien verfügbar | DOI
   
• [4]
  

  2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2939854

  Moringen, A., Fleer, S., & Ritter, H. (2019). Scaffolding Haptic Attention with Controller Gating. In I. V. Tetko, V. Kůrková, P. Karpov, & F. Theis (Eds.), Lecture Notes in Computer Science: Vol. 11727. Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation.28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part I (pp. 669-684). Cham: Springer. doi:10.1007/978-3-030-30487-4_51

  PUB | DOI | Download (ext.)
   
• [3]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933709

  Fleer, S., & Ritter, H. (2019). Skill Transfer for Mediated Interaction Learning. 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Piscataway, NJ: IEEE. doi:10.1109/humanoids.2018.8624951

  PUB | DOI | Download (ext.)
   
• [2]
  

  2019 | Konferenzbeitrag | PUB-ID: 2933988

  Melnik, A., Fleer, S., Schilling, M., & Ritter, H. (2019). Modularization of End-to-End Learning: Case Study in Arcade Games. 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Workshop on Causal Learning

  PUB | arXiv
   
• [1]
  

  2017 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2914841

  Fleer, S., & Ritter, H. (2017). Comparing Action Sets: Mutual Information as a Measure of Control. Artificial Neural Networks and Machine Learning – ICANN 2017, Lecture Notes in Computer Science, 68-75. Cham: Springer International Publishing. doi:10.1007/978-3-319-68600-4_9

  PUB | DOI