PUB - Publikationen an der Universität Bielefeld

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• [16]
  

  2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2988533

  Melnik, A.; Miasayedzenkau, M.; Makaravets, D.; Pirshtuk, D.; Akbulut, E.; Holzmann, D.; Renusch, T.; Reichert, G.; Ritter, H. (2024): Face Generation and Editing With StyleGAN: A Survey IEEE Transactions on Pattern Analysis and Machine Intelligence,46:(5): 3557-3576.

  PUB | PDF | DOI
   
• [15]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2958662

  Schilling, M.; Melnik, A.; Ohl, F. W.; Ritter, H.; Hammer, B. (2021): Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning Neural Networks,144: 699-725.

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• [14]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956099

  Melnik, A.; Lach, L. M.; Plappert, M.; Korthals, T.; Haschke, R.; Ritter, H. (2021): Using Tactile Sensing to Improve the Sample Efficiency and Performance of Deep Deterministic Policy Gradients for Simulated In-Hand Manipulation Tasks Frontiers in Robotics and AI,8:538773

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• [13]
  

  2020 | Preprint | PUB-ID: 2948844

  Harter, A.; Melnik, A.; Kumar, G.; Agarwal, D.; Garg, A.; Ritter, H. (2020): Solving Physics Puzzles by Reasoning about Paths arXiv:2011.07357

  PUB | Download (ext.) | arXiv
   
• [12]
  

  2020 | Konferenzbeitrag | PUB-ID: 2945886

  Bach, N.; Melnik, A.; Schilling, M.; Korthals, T.; Ritter, H. (2020): Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3. In: 6th International Conference, LOD 2020, Siena, Italy, Proceedings. Springer. (Lecture Notes in Computer Science, ).

  PUB | PDF
   
• [11]
  

  2020 | Konferenzbeitrag | PUB-ID: 2945884

  Bach, N.; Melnik, A.; Rosetto, F.; Ritter, H. (2020): An error-based addressing architecture for dynamic model learning. In: 6th International Conference, LOD 2020, Siena, Italy, Proceedings. Springer International Publishing. (Lecture Notes in Computer Science, ).

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• [10]
  

  2019 | Zeitschriftenaufsatz | PUB-ID: 2937519

  Korthals, T.; Melnik, A.; Hesse, M.; Leitner, J. (2019): Multisensory Assisted In-hand Manipulation of Objects with a Dexterous Hand 2019 IEEE International Conference on Robotics and Automation Workshop on Integrating Vision and Touch for Multimodal and Cross-modal Perception, (ViTac) 2019, Montreal, CA, May 20-25, 2019, 1-2.

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• [9]
  

  2019 | Zeitschriftenaufsatz | PUB-ID: 2937517

  Konen, K.; Korthals, T.; Melnik, A.; Schilling, M. (2019): Biologically-Inspired Deep Reinforcement Learning of Modular Control for a Six-Legged Robot 2019 IEEE International Conference on Robotics and Automation Workshop on Learning Legged Locomotion Workshop, (ICRA) 2019, Montreal, CA, May 20-25, 2019, 1-3.

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• [8]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2939836

  Melnik, A.; Bramlage, L.; Voss, H.; Rossetto, F.; Ritter, H. (2019): Combining Causal Modelling and Deep Reinforcement Learning for Autonomous Agents in Minecraft.

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• [7]
  

  2019 | Konferenzbeitrag | PUB-ID: 2937521

  Korthals, T.; Hesse, M.; Leitner, J.; Melnik, A.; Rückert, U. (2019): Jointly Trained Variational Autoencoder for Multi-Modal Sensor Fusion. In: 22st International Conference on Information Fusion, (FUSION) 2019, Ottawa, CA, July 2-5, 2019. S. 1-8.

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• [6]
  

  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. In: 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Workshop on Causal Learning.

  PUB | arXiv
   
• [5]
  

  2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2932767

  Melnik, A.; Schueler, F.; Rothkopf, C. A.; Koenig, P. (2018): The World as an External Memory. The Price of Saccades in a Sensorimotor Task FRONTIERS IN BEHAVIORAL NEUROSCIENCE,12:253

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• [4]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2940661

  Kidziński, Ł.; Mohanty, S. P.; Ong, C.; Huang, Z.; Zhou, S.; Pechenko, A.; Stelmaszczyk, A.; Jarosik, P.; Pavlov, M.; Kolesnikov, S.; Plis, S.; Chen, Z.; Zhang, Z.; Chen, J.; Shi, J.; Zheng, Z.; Yuan, C.; Lin, Z.; Michalewski, H.; Miłoś, P.; Osiński, B.; Melnik, A.; Schilling, M.; Ritter, H.; Carroll, S.; Hicks, J.; Levine, S.; Salathé, M.; Delp, S. (2018): Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments.

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

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2934190

  Schilling, M.; Melnik, A. (2018): An Approach to Hierarchical Deep Reinforcement Learning for a Decentralized Walking Control Architecture. In: Alexei V. Samsonovic (Hrsg.): Biologically Inspired Cognitive Architectures 2018. Proceedings of the Ninth Annual Meeting of the BICA Society. Cham: Springer . (Advances in Intelligent Systems and Computing, 848). S. 272-282.

  PUB | DOI
   
• [2]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2940668

  Melnik, A.; Legkov, P.; Izdebski, K.; Kärcher, S. M.; Hairston, W. D.; Ferris, D. P.; König, P. (2017): Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data? Frontiers in Human Neuroscience,11: 150.

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• [1]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2940669

  Melnik, A.; Hairston, W. D.; Ferris, D. P.; König, P. (2017): EEG correlates of sensorimotor processing: independent components involved in sensory and motor processing Scientific Reports,7:(1):4461

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