16 Publikationen
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2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2988533Melnik, A., Miasayedzenkau, M., Makaravets, D., Pirshtuk, D., Akbulut, E., Holzmann, D., Renusch, T., et al. (2024). Face Generation and Editing With StyleGAN: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5), 3557-3576. https://doi.org/10.1109/TPAMI.2024.3350004PUB | PDF | DOI
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2958662Schilling, 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. https://doi.org/10.1016/j.neunet.2021.09.017PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956099Melnik, 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. https://doi.org/10.3389/frobt.2021.538773PUB | PDF | DOI | Download (ext.) | WoS | PubMed | Europe PMC
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2020 | Preprint | PUB-ID: 2948844Harter, A., Melnik, A., Kumar, G., Agarwal, D., Garg, A., & Ritter, H. (2020). Solving Physics Puzzles by Reasoning about Paths. arXiv:2011.07357PUB | Download (ext.) | arXiv
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2020 | Konferenzbeitrag | PUB-ID: 2945886Bach, N., Melnik, A., Schilling, M., Korthals, T., & Ritter, H. (2020). Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3. 6th International Conference, LOD 2020, Siena, Italy, Proceedings, Lecture Notes in Computer Science Springer.PUB | PDF
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2020 | Konferenzbeitrag | PUB-ID: 2945884Bach, N., Melnik, A., Rosetto, F., & Ritter, H. (2020). An error-based addressing architecture for dynamic model learning. 6th International Conference, LOD 2020, Siena, Italy, Proceedings, Lecture Notes in Computer Science Springer International Publishing.PUB | PDF
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2019 | Zeitschriftenaufsatz | PUB-ID: 2937519Korthals, 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.PUB | PDF
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2019 | Zeitschriftenaufsatz | PUB-ID: 2937517Konen, 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.PUB | PDF
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2939836Melnik, A., Bramlage, L., Voss, H., Rossetto, F., & Ritter, H. (2019). Combining Causal Modelling and Deep Reinforcement Learning for Autonomous Agents in Minecraft. Presented at the 4th Workshop on Semantic Policy and Action Representations for Autonomous Robots at IROS 2019, Macau.PUB | Download (ext.)
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2932767Melnik, 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. doi:10.3389/fnbeh.2018.00253PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2940661Kidziński, Ł., Mohanty, S. P., Ong, C., Huang, Z., Zhou, S., Pechenko, A., Stelmaszczyk, A., et al. (2018). Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. Presented at the 31nd Conference on Neural Information Processing Systems (NIPS 2017), Competition Track, Long Beach, USA.PUB | Download (ext.) | arXiv
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2934190Schilling, M., & Melnik, A. (2018). An Approach to Hierarchical Deep Reinforcement Learning for a Decentralized Walking Control Architecture. In A. V. Samsonovic (Ed.), Advances in Intelligent Systems and Computing: Vol. 848. Biologically Inspired Cognitive Architectures 2018. Proceedings of the Ninth Annual Meeting of the BICA Society (pp. 272-282). Cham: Springer . doi:10.1007/978-3-319-99316-4_36PUB | DOI
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2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2940668Melnik, 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. doi:10.3389/fnhum.2017.00150PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
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2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2940669Melnik, 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. doi:10.1038/s41598-017-04757-8PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC