J. Michael Herrmann

Dario Farina, Bernhard Graimann, Nina Rudigkeit, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

The neural representation of time

Joachim Haß, J. Michael Herrmann, 2012 .

Recurrence-Based Estimation of Time-Distortion Functions for ERP Waveform Reconstruction

J. Michael Herrmann, J. M. Herrmann, Matthias Ihrke, 2011, Int. J. Neural Syst..

Compositionality of arm movements can be realized by propagating synchrony

Markus Diesmann, J. Michael Herrmann, Abigail Morrison, 2010, Journal of Computational Neuroscience.

Synaptic depression in associative memory networks

J. Michael Herrmann, Theo Geisel, Dmitri Bibitchkov, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Reflexive Reinforcement Learning: Methods for Self-Referential Autonomous Learning

J. Michael Herrmann, J. M. Herrmann, B. I. Lyons, 2020, IJCCI.

Measuring topology preservation in maps of real-world data

Thomas Villmann, J. Michael Herrmann, Hans-Ulrich Bauer, 1997, ESANN.

Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement

Thomas Villmann, Thomas Martinetz, Ralf Der, 1994, Fuzzy Days.

INTERDISCIPLINARY PHYSICS | REVIEW ARTICLE Neuronal avalanches in complex networks

J. Michael Herrmann, J. M. Herrmann, Victor Hernandez-Urbina, 2016 .

The critical state in particle swarm optimisation

J. Michael Herrmann, Thomas Joyce, Adam Erskine, 2018 .

The Voynich Manuscript is Written in Natural Language: The Pahlavi Hypothesis pdf

J. Michael Herrmann, J. Herrmann, 2017, ArXiv.

Analysis of correlated activity in fMRI data by artificial neural networks

Silke Dodel, J. Michael Herrmann, Marotesa Voultsidou, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

Tipping the scales: guidance and intrinsically motivated behavior

J. Michael Herrmann, Georg Martius, 2011, ECAL.

Forward-looking sonar image mosaicking by feature tracking

J. Michael Herrmann, Shuo Li, Kaizhou Liu, 2016, 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO).

A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior

Ralf Der, J. Michael Herrmann, Frank Hesse, 2009, Algorithms.

Self-organisation of Spatial Behaviour in a Kilobot Swarm

J. Michael Herrmann, Calum Imrie, 2017, Living Machines.

Robot Exploration by Subjectively Maximizing Objective Information Gain

J. Michael Herrmann, Klaus Pawelzik, Bailu Si, 2004, 2004 IEEE International Conference on Robotics and Biomimetics.

Guided Self-organisation for Autonomous Robot Development

Ralf Der, J. Michael Herrmann, Georg Martius, 2007, ECAL.

A feature-binding model with localized excitations

J. Michael Herrmann, Theo Geisel, J. M. Herrmann, 2007, Neurocomputing.

Modulated Exploratory Dynamics Can Shape Self-Organized Behavior

Ralf Der, J. Michael Herrmann, Frank Hesse, 2009, Adv. Complex Syst..

Evaluation of Internal Models in Autonomous Learning

J. Michael Herrmann, J. M. Herrmann, Simón C. Smith, 2019, IEEE Transactions on Cognitive and Developmental Systems.

Stimulus-Independent Data Analysis for fMRI

Silke Dodel, J. Michael Herrmann, Theo Geisel, 2001, Emergent Neural Computational Architectures Based on Neuroscience.

Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots

J. Michael Herrmann, Georg Martius, G. Martius, 2010, SAB.

Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches

J. Michael Herrmann, Theo Geisel, J. M. Herrmann, 2005, NIPS.

Structure from behavior in autonomous agents

J. Michael Herrmann, Georg Martius, Katja Fiedler, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Simultaneous self-organization of place and direction selectivity in a neural model of self-localization

J. Michael Herrmann, Klaus Pawelzik, 1999, Neurocomputing.

Statistical Baselines from Random Matrix Theory

J. Michael Herrmann, Marotesa Voultsidou, M. Voultsidou, 2008, IDEAL.

Evolutionary Design of an Adaptive Dynamic Walker

Joachim Haß, J. Michael Herrmann, Theo Geisel, 2005 .

Shaping of Receptive Fields in the Visual Cortex During Retinal Maturation

J. Michael Herrmann, Theo Geisel, Norbert Michael Mayer, 2004, Journal of Computational Neuroscience.

Lagged correlation-based deep learning for directional trend change prediction in financial time series

J. Michael Herrmann, J. M. Herrmann, Ben Moews, 2018, Expert Syst. Appl..

Signatures of natural image statistics in cortical simple cell receptive fields

J. Michael Herrmann, Theo Geisel, Norbert Michael Mayer, 2001, Neurocomputing.

CriPS: Critical Dynamics in Particle Swarm Optimization pdf

J. Michael Herrmann, Adam Erskine, 2014, ArXiv.

Critical branching processes in neural networks

J. Michael Herrmann, Anna Levina, Manfred Denker, 2007 .

Criticality of avalanche dynamics in adaptive recurrent networks

J. Michael Herrmann, Udo Ernst, J. M. Herrmann, 2006, Neurocomputing.

Cell Division Behaviour in a Heterogeneous Swarm Environment

J. Michael Herrmann, Adam Erskine, Adam Erskine, 2013, ECAL.

Instabilities in self-organized feature maps with short neighbourhood range

Ralf Der, J. Michael Herrmann, 1994, ESANN.

Two-dimensional forward-looking sonar image registration by maximization of peripheral mutual information

J. Michael Herrmann, Kaizhou Liu, Xisheng Feng, 2017 .

Variants of guided self-organization for robot control

J. Michael Herrmann, Georg Martius, 2011, Theory in Biosciences.

Self-Localization of Autonomous Robots by Hidden Representations

J. Michael Herrmann, Theo Geisel, Klaus Pawelzik, 1999, Auton. Robots.

Statistical Models of Neural Activity, Criticality, and Zipf’s Law

J. Michael Herrmann, Matthias H. Hennig, J. M. Herrmann, 2018, Springer Series on Bio- and Neurosystems.

Self-Organization of Exploratory Control

J. Michael Herrmann, Frank Hesse, Georg Martius, 2010 .

Topology preservation in self-organizing feature maps: exact definition and measurement

Thomas Villmann, Thomas Martinetz, Ralf Der, 1997, IEEE Trans. Neural Networks.

The DIAMOND Model: Deep Recurrent Neural Networks for Self-Organizing Robot Control

J. Michael Herrmann, Bailu Si, J. M. Herrmann, 2020, Frontiers in Neurorobotics.

Robot Learning by Guided Self-Organization

Ralf Der, J. Michael Herrmann, Georg Martius, 2014 .

Learning predictive representations

J. Michael Herrmann, Theo Geisel, Klaus Pawelzik, 2000, Neurocomputing.

Retinotopy and spatial phase in topographic maps

J. Michael Herrmann, Theo Geisel, Norbert Michael Mayer, 2000, Neurocomputing.

Self-organized Criticality via Retro-Synaptic Signals

J. Michael Herrmann, J. M. Herrmann, Victor Hernandez-Urbina, 2017, Front. Phys..

Homeokinetic prosthetic control: collaborative selection of myosignal features

J. Michael Herrmann, Frank Hesse, 2010, 19th International Symposium in Robot and Human Interactive Communication.

Structure formation in visual cortex based on a curved feature space

J. Michael Herrmann, Theo Geisel, Norbert Michael Mayer, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Neural networks approach to clustering of activity in fMRI data

Silke Dodel, J. Michael Herrmann, J. M. Herrmann, 2005, IEEE Transactions on Medical Imaging.

Critical dynamics in homeostatic memory networks

J. Michael Herrmann, Sakyasingha Dasgupta, 2011 .

Critical Parameters in Particle Swarm Optimisation pdf

J. Michael Herrmann, Thomas Joyce, Adam Erskine, 2015, ArXiv.

Critical dynamics in associative memory networks

J. Michael Herrmann, Theo Geisel, J. M. Herrmann, 2013, Front. Comput. Neurosci..

Homeokinetic proportional control of myoelectric prostheses

J. Michael Herrmann, Frank Hesse, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Symmetries, non-Euclidean metrics, and patterns in a Swift–Hohenberg model of the visual cortex

Minoru Asada, J. Michael Herrmann, Norbert Michael Mayer, 2008, Biological Cybernetics.

Localized activations in a simple neural field model

J. Michael Herrmann, Theo Geisel, Hecke Schrobsdorff, 2005, Neurocomputing.

A Review of No Free Lunch Theorems, and Their Implications for Metaheuristic Optimisation

J. Michael Herrmann, Thomas Joyce, J. M. Herrmann, 2018 .

CriPS: Critical Particle Swarm Optimisation

J. Michael Herrmann, Adam Erskine, 2015, ECAL.

A neurocomputational model for optimal temporal processing

Joachim Haß, J. Michael Herrmann, Stefan Blaschke, 2008, Journal of Computational Neuroscience.

Cell-Division Behavior in a Heterogeneous Swarm Environment

J. Michael Herrmann, Adam Erskine, Adam Erskine, 2015, Artificial Life.

Spatial Feature Extraction for Classification of Nonstationary Myoelectric Signals

J. Michael Herrmann, David Hofmann, J. M. Herrmann, 2012, 2012 11th International Conference on Machine Learning and Applications.

Time behavior of topological ordering in self-organizing feature mapping

Thomas Villmann, Ralf Der, J. Michael Herrmann, 1997, Biological Cybernetics.

Dynamical Systems for Predictive Control of Autonomous Robots

J. Michael Herrmann, 2001 .

Optimal Mass Distribution for Passivity-Based Bipedal Robots

Joachim Haß, J. Michael Herrmann, Theo Geisel, 2006, Int. J. Robotics Res..

Stability of Localized Patterns in Neural Fields

J. Michael Herrmann, Konstantin Doubrovinski, 2009, Neural Computation.

A computational approach to negative priming

J. Michael Herrmann, J. M. Herrmann, Marcus Hasselhorn, 2007, Connect. Sci..

Dynamical systems for predictive control of autonomous robots

J. Michael Herrmann, 2001, Theory in Biosciences.

Statistical Analysis of Sample-Size Effects in ICA

Fabian J. Theis, J. Michael Herrmann, Fabian J Theis, 2007, IDEAL.

Neural maps and topographic vector quantization

Thomas Villmann, J. Michael Herrmann, Hans-Ulrich Bauer, 1999, Neural Networks.

Denoising and Averaging Techniques for Electrophysiological Data

J. Michael Herrmann, J. M. Herrmann, Matthias Ihrke, 2009 .

Evolutionary Selective Imitation: Interpretable Agents by Imitation Learning Without a Demonstrator pdf

J. Michael Herrmann, J. M. Herrmann, Roy Eliya, 2020, ArXiv.

Modeling Structure and Dynamics of Selective Attention

J. Michael Herrmann, J. M. Herrmann, Matthias Ihrke, 2012, BICA.

Compensation for Speed-of-Processing Effects in EEG-Data Analysis

J. Michael Herrmann, J. M. Herrmann, Matthias Ihrke, 2008, IDEAL.

Self-Organisation of Generic Policies in Reinforcement Learning

J. Michael Herrmann, Simón C. Smith, Simón C. Smith, 2013, ECAL.

Curved feature metrics in models of visual cortex

J. Michael Herrmann, Theo Geisel, Norbert Michael Mayer, 2002, Neurocomputing.

Emergence of Interaction among Adaptive Agents

Stefano Nolfi, J. Michael Herrmann, Georg Martius, 2008, SAB.

Homeokinetic Reinforcement Learning

J. Michael Herrmann, J. M. Herrmann, Simón C. Smith, 2011, PSL.

Gain-based Exploration: From Multi-armed Bandits to Partially Observable Environments

J. Michael Herrmann, Klaus Pawelzik, Bailu Si, 2007, Third International Conference on Natural Computation (ICNC 2007).

The paradox of choice in evolving swarms: information overload leads to limited sensing

J. Michael Herrmann, Olaf Witkowski, Calum C. Imrie, 2021, GECCO.

Localization of brain activity - blind separation for fMRI data

Silke Dodel, J. Michael Herrmann, Theo Geisel, 2000, Neurocomputing.

Emergent Neural Computational Architectures based on

Stefan Wermter, Silke Dodel, Jim Austin, 2001 .

Theoretical neuroscience of self‐organized criticality: from formal approaches to realistic models

J. Michael Herrmann, Theo Geisel, J. M. Herrmann, 2014 .

Identity Negative Priming: A Phenomenon of Perception, Recognition or Selection?

J. Michael Herrmann, J. M. Herrmann, Marcus Hasselhorn, 2012, PloS one.

Prior parameter estimation for Ising-MRF-based sonar image segmentation by local center-encoding

J. Michael Herrmann, Xisheng Feng, Bailu Si, 2015, OCEANS 2015 - Genova.

Natural Vocalizations in the Mammalian Inferior Colliculus are Broadly Encoded by a Small Number of Independent Multi-Units

Florentin Wörgötter, J. Michael Herrmann, J. M. Herrmann, 2016, Front. Neural Circuits.

Cross-Modal Distortion of Time Perception: Demerging the Effects of Observed and Performed Motion

J. Michael Herrmann, Joachim Hass, Stefan Blaschke, 2012, PloS one.