Quantum Coupled Mutation Finder: Predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming. - Mehmet Gültas; Güncel Düzgün; Sebastian Herzog; Sven Joachim Jäger; Cornelia Meckbach; Edgar Wingender; Stephan Waack (BMC Bioinform., 2014)

Optimal trajectory generation for generalization of discrete movements with boundary conditions. - Sebastian Herzog; Florentin Wörgötter; Tomas Kulvicius (IROS, 2016)

Transfer entropy-based feedback improves performance in artificial neural networks. - Sebastian Herzog; Christian Tetzlaff; Florentin Wörgötter (CoRR, 2017)

Generation of movements with boundary conditions based on optimal control theory. - Sebastian Herzog; Florentin Wörgötter; Tomas Kulvicius (Robotics Auton. Syst., 2017)

Data-Driven Modeling and Prediction of Complex Spatio-Temporal Dynamics in Excitable Media. - Sebastian Herzog; Florentin Wörgötter; Ulrich Parlitz (Frontiers Appl. Math. Stat., 2018)

One-Shot Multi-Path Planning for Robotic Applications Using Fully Convolutional Networks. - Tomas Kulvicius; Sebastian Herzog; Timo Lüddecke; Minija Tamosiunaite; Florentin Wörgötter (ICRA, 2020)

Generation of Paths in a Maze using a Deep Network without Learning. - Tomas Kulvicius; Sebastian Herzog; Minija Tamosiunaite; Florentin Wörgötter (CoRR, 2020)

One-shot path planning for multi-agent systems using fully convolutional neural network. - Tomas Kulvicius; Sebastian Herzog; Timo Lüddecke; Minija Tamosiunaite; Florentin Wörgötter (CoRR, 2020)

Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders. - Sebastian Herzog; Roland S. Zimmermann; Johannes Abele; Stefan Luther; Ulrich Parlitz (Frontiers Appl. Math. Stat., 2020)

One-Shot Multi-Path Planning Using Fully Convolutional Networks in a Comparison to Other Algorithms. - Tomas Kulvicius; Sebastian Herzog; Timo Lüddecke; Minija Tamosiunaite; Florentin Wörgötter (Frontiers Neurorobotics, 2020)

Evolving artificial neural networks with feedback. - Sebastian Herzog; Christian Tetzlaff; Florentin Wörgötter (Neural Networks, 2020)

A Probabilistic Particle Tracking Framework for Guided and Brownian Motion Systems with High Particle Densities. - Sebastian Herzog; Daniel Schiepel; Isabella Guido; Robin Barta; Claus Wagner (SN Comput. Sci., 2021)

Data-driven modelling of non-linear systems by means of artificial neural network hybrids. - Sebastian Herzog (2021)

Application of neural ordinary differential equations to the prediction of multi-agent systems. - Sebastian Herzog; Florentin Wörgötter (Artif. Life Robotics, 2022)

Finding Optimal Paths Using Networks Without Learning - Unifying Classical Approaches. - Tomas Kulvicius; Sebastian Herzog; Minija Tamosiunaite; Florentin Wörgötter (IEEE Trans. Neural Networks Learn. Syst., 2022)

proPTV: A probability-based particle tracking velocimetry framework. - Robin Barta; Christian Bauer; Sebastian Herzog; Daniel Schiepel; Claus Wagner (J. Comput. Phys., 2024)