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Transfer entropy-based feedback improves performance in artificial neural networks., , and . CoRR, (2017)Generation of movements with boundary conditions based on optimal control theory., , and . Robotics Auton. Syst., (2017)Data-Driven Modeling and Prediction of Complex Spatio-Temporal Dynamics in Excitable Media., , and . Frontiers Appl. Math. Stat., (2018)A Probabilistic Particle Tracking Framework for Guided and Brownian Motion Systems with High Particle Densities., , , , and . SN Comput. Sci., 2 (6): 485 (2021)Quantum Coupled Mutation Finder: Predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming., , , , , , and . BMC Bioinform., (2014)Generation of Paths in a Maze using a Deep Network without Learning., , , and . CoRR, (2020)Application of neural ordinary differential equations to the prediction of multi-agent systems., and . Artif. Life Robotics, 27 (2): 213-217 (2022)One-Shot Multi-Path Planning Using Fully Convolutional Networks in a Comparison to Other Algorithms., , , , and . Frontiers Neurorobotics, (2020)Data-driven modelling of non-linear systems by means of artificial neural network hybrids.. University of Göttingen, Germany, (2021)One-Shot Multi-Path Planning for Robotic Applications Using Fully Convolutional Networks., , , , and . ICRA, page 1460-1466. IEEE, (2020)