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Andrew Melnik
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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
1122017
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
922018
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
572017
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
262021
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
252019
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
222021
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
222020
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
222018
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
182019
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
162019
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
152019
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
152019
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
132024
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
122022
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
122018
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
112022
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
102023
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
102021
Contrastive Language, Action, and State Pre-training for Robot Learning
K Rana, A Melnik, N Sünderhauf
arXiv preprint arXiv:2304.10782, 2023
82023
Planning with RL and episodic-memory behavioral priors
S Beohar, A Melnik
arXiv preprint arXiv:2207.01845, 2022
82022
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