| Systems, subjects, sessions: to what extent do these factors influence EEG data? A Melnik, P Legkov, K Izdebski, SM Kärcher, WD Hairston, DP Ferris, ... Frontiers in human neuroscience 11, 150, 2017 | 127 | 2017 |
| Learning to run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ... The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018 | 99 | 2018 |
| EEG correlates of sensorimotor processing: independent components involved in sensory and motor processing A Melnik, WD Hairston, DP Ferris, P König Scientific Reports 7 (1), 4461, 2017 | 65 | 2017 |
| Using tactile sensing to improve the sample efficiency and performance of deep deterministic policy gradients for simulated in-hand manipulation tasks A Melnik, L Lach, M Plappert, T Korthals, R Haschke, H Ritter Frontiers in Robotics and AI 8, 538773, 2021 | 35 | 2021 |
| The world as an external memory: the price of saccades in a sensorimotor task A Melnik, F Schüler, CA Rothkopf, P König Frontiers in behavioral neuroscience 12, 253, 2018 | 28 | 2018 |
| Face generation and editing with stylegan: A survey A Melnik, M Miasayedzenkau, D Makaravets, D Pirshtuk, E Akbulut, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 27 | 2024 |
| Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning M Schilling, A Melnik, FW Ohl, HJ Ritter, B Hammer Neural Networks 144, 699-725, 2021 | 27 | 2021 |
| An approach to hierarchical deep reinforcement learning for a decentralized walking control architecture M Schilling, A Melnik Biologically Inspired Cognitive Architectures 2018: Proceedings of the Ninth …, 2019 | 25 | 2019 |
| Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3 N Bach, A Melnik, M Schilling, T Korthals, H Ritter 6th International Conference, LOD 2020, Proceedings, 2020 | 24 | 2020 |
| Tactile Sensing and Deep Reinforcement Learning for In-Hand Manipulation Tasks A Melnik, L Lach, M Plappert, T Korthals, R Haschke, H Ritter IROS Workshop on Autonomous Object Manipulation, 2019 | 24 | 2019 |
| Traffic4cast at NeurIPS 2021-Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes C Eichenberger, M Neun, H Martin, P Herruzo, M Spanring, Y Lu, S Choi, ... NeurIPS 2021 Competitions and Demonstrations Track, 97-112, 2022 | 20 | 2022 |
| Jointly trained variational autoencoder for multi-modal sensor fusion T Korthals, M Hesse, J Leitner, A Melnik, U Rückert 2019 22th International Conference on Information Fusion (FUSION), 1-8, 2019 | 17 | 2019 |
| Biologically-Inspired Deep Reinforcement Learning of Modular Control for a Six-Legged Robot K Konen, T Korthals, A Melnik, M Schilling 2019 IEEE International Conference on Robotics and Automation Workshop on …, 2019 | 16 | 2019 |
| Embodied cognition P König, A Melnik, C Goeke, AL Gert, SU König, TC Kietzmann 2018 6th International Conference on Brain-Computer Interface (BCI), 1-4, 2018 | 16 | 2018 |
| Modularization of end-to-end learning: Case study in arcade games A Melnik, S Fleer, M Schilling, H Ritter arXiv preprint arXiv:1901.09895, 2019 | 15 | 2019 |
| Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020 WH Guss, S Milani, N Topin, B Houghton, S Mohanty, A Melnik, A Harter, ... NeurIPS 2020 Competition and Demonstration Track, 233-252, 2021 | 13 | 2021 |
| Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition S Milani, A Kanervisto, K Ramanauskas, S Schulhoff, B Houghton, ... arXiv preprint arXiv:2303.13512, 2023 | 12 | 2023 |
| Critic guided segmentation of rewarding objects in first-person views A Melnik, A Harter, C Limberg, K Rana, N Sünderhauf, H Ritter KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI …, 2021 | 11 | 2021 |
| Behavioral Cloning via Search in Video PreTraining Latent Space F Malato, F Leopold, A Raut, V Hautamäki, A Melnik arXiv preprint arXiv:2212.13326, 2022 | 10 | 2022 |
| Transfer learning with jukebox for music source separation W Zai El Amri, O Tautz, H Ritter, A Melnik IFIP International Conference on Artificial Intelligence Applications and …, 2022 | 9 | 2022 |
Helge RitterProfessor of Neuroinformatics, Bielefeld UniversityVerified email at techfak.uni-bielefeld.de
