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J. Michael Herrmann
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2020 – today
- 2024
- [j38]Han Li
, Jin Sun
Beyond jamming grippers: granular material in robotics. Adv. Robotics 38(11): 715-729 (2024) - 2023
- [c37]Yurdusev Yakup Akan
Stability, Entropy and Performance in PSO. GECCO Companion 2023: 811-814 - 2022
- [c36]Isobel Voysey, Lynne Baillie
Influence of Animallike Affective Non-verbal Behavior on Children's Perceptions of a Zoomorphic Robot. RO-MAN 2022: 1443-1450 - 2021
- [c35]Calum C. Imrie, J. Michael Herrmann, Olaf Witkowski:
The paradox of choice in evolving swarms: information overload leads to limited sensing. GECCO 2021: 22-30 - 2020
- [j37]Simón C. Smith, Richard Dharmadi, Calum Imrie, Bailu Si, J. Michael Herrmann:
The DIAMOND Model: Deep Recurrent Neural Networks for Self-Organizing Robot Control. Frontiers Neurorobotics 14: 62 (2020) - [c34]B. I. Lyons, J. Michael Herrmann:
Reflexive Reinforcement Learning: Methods for Self-Referential Autonomous Learning. IJCCI 2020: 381-388 - [i5]Roy Eliya, J. Michael Herrmann:
Evolutionary Selective Imitation: Interpretable Agents by Imitation Learning Without a Demonstrator. CoRR abs/2009.08403 (2020)
2010 – 2019
- 2019
- [j36]Min Jiang, Xisheng Feng, Sanming Song
Underwater Loop-Closure Detection for Mechanical Scanning Imaging Sonar by Filtering the Similarity Matrix With Probability Hypothesis Density Filter. IEEE Access 7: 166614-166628 (2019) - [j35]Ben Moews
Lagged correlation-based deep learning for directional trend change prediction in financial time series. Expert Syst. Appl. 120: 197-206 (2019) - [j34]Simón C. Smith, J. Michael Herrmann
Evaluation of Internal Models in Autonomous Learning. IEEE Trans. Cogn. Dev. Syst. 11(4): 463-472 (2019) - 2018
- [i4]Ben Moews, J. Michael Herrmann, Gbenga Ibikunle:
Lagged correlation-based deep learning for directional trend change prediction in financial time series. CoRR abs/1811.11287 (2018) - 2017
- [j33]Adam Erskine, Thomas Joyce, J. Michael Herrmann
Stochastic stability of particle swarm optimisation. Swarm Intell. 11(3-4): 295-315 (2017) - [c33]Calum Imrie, J. Michael Herrmann:
Self-organisation of Spatial Behaviour in a Kilobot Swarm. Living Machines 2017: 551-561 - [i3]J. Michael Herrmann:
The Voynich Manuscript is Written in Natural Language: The Pahlavi Hypothesis. CoRR abs/1709.01634 (2017) - 2016
- [j32]Sanming Song, Bailu Si, J. Michael Herrmann, Xisheng Feng:
Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field. IEEE Trans. Image Process. 25(5): 2324-2336 (2016) - [c32]Adam Erskine, Thomas Joyce, J. Michael Herrmann:
Parameter Selection in Particle Swarm Optimisation from Stochastic Stability Analysis. ANTS Conference 2016: 161-172 - [c31]Sanming Song, J. Michael Herrmann, Kaizhou Liu, Shuo Li
Forward-looking sonar image mosaicking by feature tracking. ROBIO 2016: 1613-1618 - 2015
- [j31]Adam Erskine, J. Michael Herrmann:
Cell-Division Behavior in a Heterogeneous Swarm Environment. Artif. Life 21(4): 481-500 (2015) - [c30]Adam Erskine, J. Michael Herrmann:
CriPS: Critical Particle Swarm Optimisation. ECAL 2015: 207-214 - [i2]J. Michael Herrmann, Adam Erskine, Thomas Joyce:
Critical Parameters in Particle Swarm Optimisation. CoRR abs/1511.06248 (2015) - 2014
- [i1]Adam Erskine, J. Michael Herrmann:
CriPS: Critical Dynamics in Particle Swarm Optimization. CoRR abs/1402.6888 (2014) - 2013
- [j30]Maximilian Uhlig
Critical dynamics in associative memory networks. Frontiers Comput. Neurosci. 7: 87 (2013) - [c29]Adam Erskine, J. Michael Herrmann:
Cell Division Behaviour in a Heterogeneous Swarm Environment. ECAL 2013: 35-42 - [c28]Simón C. Smith, J. Michael Herrmann:
Self-Organisation of Generic Policies in Reinforcement Learning. ECAL 2013: 641-648 - [c27]Sebastian Amsuss, Liliana Paredes, Nina Rudigkeit, Bernhard Graimann, J. Michael Herrmann, Dario Farina:
Long term stability of surface EMG pattern classification for prosthetic control. EMBC 2013: 3622-3625 - 2012
- [j29]Joachim Hass
The Neural Representation of Time: An Information-Theoretic Perspective. Neural Comput. 24(6): 1519-1552 (2012) - [j28]Georg Martius
Variants of guided self-organization for robot control. Theory Biosci. 131(3): 129-137 (2012) - [c26]Hecke Schrobsdorff, Matthias Ihrke
Modeling Structure and Dynamics of Selective Attention. BICA 2012: 287-295 - [c25]David Hofmann, J. Michael Herrmann:
Spatial Feature Extraction for Classification of Nonstationary Myoelectric Signals. ICMLA (2) 2012: 416-421 - 2011
- [j27]Matthias Ihrke, Hecke Schrobsdorff, J. Michael Herrmann:
Recurrence-Based Estimation of Time-Distortion Functions for ERP Waveform Reconstruction. Int. J. Neural Syst. 21(1): 65-78 (2011) - [j26]Alexander Hanuschkin, J. Michael Herrmann, Abigail Morrison
Compositionality of arm movements can be realized by propagating synchrony. J. Comput. Neurosci. 30(3): 675-697 (2011) - [c24]Georg Martius, J. Michael Herrmann:
Tipping the scales: guidance and intrinsically motivated behavior. ECAL 2011: 506-513 - [c23]Simón C. Smith, J. Michael Herrmann:
Homeokinetic Reinforcement Learning. PSL 2011: 82-91 - 2010
- [c22]Frank Hesse, J. Michael Herrmann:
Homeokinetic proportional control of myoelectric prostheses. IROS 2010: 1786-1791 - [c21]Frank Hesse, J. Michael Herrmann:
Homeokinetic prosthetic control: collaborative selection of myosignal features. RO-MAN 2010: 410-415 - [c20]Georg Martius
Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots. SAB 2010: 50-61
2000 – 2009
- 2009
- [j25]Frank Hesse, Ralf Der, J. Michael Herrmann:
Modulated Exploratory Dynamics Can Shape Self-Organized Behavior. Adv. Complex Syst. 12(3): 273-291 (2009) - [j24]Frank Hesse, Georg Martius, Ralf Der, J. Michael Herrmann:
A Sensor-Based Learning Algorithm for the Self-Organization of Robot Behavior. Algorithms 2(1): 398-409 (2009) - [j23]Konstantin Doubrovinski, J. Michael Herrmann:
Stability of Localized Patterns in Neural Fields. Neural Comput. 21(4): 1125-1144 (2009) - [c19]Matthias Ihrke
Recurrence-Based Synchronization of Single Trials for EEG-Data Analysis. IDEAL 2009: 118-125 - 2008
- [j22]Norbert Michael Mayer, Matthew Browne
Symmetries, non-Euclidean metrics, and patterns in a Swift-Hohenberg model of the visual cortex. Biol. Cybern. 99(1): 63-78 (2008) - [j21]Joachim Haß
A neurocomputational model for optimal temporal processing. J. Comput. Neurosci. 25(3): 449-464 (2008) - [c18]Matthias Ihrke, Hecke Schrobsdorff, J. Michael Herrmann:
Compensation for Speed-of-Processing Effects in EEG-Data Analysis. IDEAL 2008: 354-361 - [c17]Marotesa Voultsidou, J. Michael Herrmann:
Statistical Baselines from Random Matrix Theory. IDEAL 2008: 362-369 - [c16]Georg Martius
Structure from behavior in autonomous agents. IROS 2008: 858-862 - [c15]Georg Martius, Stefano Nolfi, J. Michael Herrmann:
Emergence of Interaction among Adaptive Agents. SAB 2008: 457-466 - 2007
- [j20]Hecke Schrobsdorff, Matthias Ihrke, B. Kabisch, J. Behrendt, Marcus Hasselhorn, J. Michael Herrmann:
A computational approach to negative priming. Connect. Sci. 19(3): 203-221 (2007) - [j19]Hecke Schrobsdorff, J. Michael Herrmann, Theo Geisel:
A feature-binding model with localized excitations. Neurocomputing 70(10-12): 1706-1710 (2007) - [j18]Anna Levina
Criticality of avalanche dynamics in adaptive recurrent networks. Neurocomputing 70(10-12): 1877-1881 (2007) - [c14]Georg Martius, J. Michael Herrmann, Ralf Der:
Guided Self-organisation for Autonomous Robot Development. ECAL 2007: 766-775 - [c13]Bailu Si, J. Michael Herrmann, Klaus Pawelzik:
Gain-based Exploration: From Multi-armed Bandits to Partially Observable Environments. ICNC (1) 2007: 177-182 - [c12]J. Michael Herrmann, Fabian J. Theis:
Statistical Analysis of Sample-Size Effects in ICA. IDEAL 2007: 416-425 - 2006
- [j17]Joachim Haß
Optimal Mass Distribution for Passivity-Based Bipedal Robots. Int. J. Robotics Res. 25(11): 1087-1098 (2006) - 2005
- [j16]J. Michael Herrmann, Hecke Schrobsdorff, Theo Geisel:
Localized activations in a simple neural field model. Neurocomputing 65-66: 679-684 (2005) - [j15]Marotesa Voultsidou, Silke Dodel, J. Michael Herrmann:
Neural Networks Approach to Clustering of Activity in fMRI Data. IEEE Trans. Medical Imaging 24(8): 987-996 (2005) - [c11]Anna Levina, J. Michael Herrmann, Theo Geisel:
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches. NIPS 2005: 771-778 - 2004
- [c10]Marotesa Voultsidou, Silke Dodel, J. Michael Herrmann:
Analysis of Correlated Activity in fMRI Data by Artificial Neural Networks. ISBI 2004: 872-875 - [c9]Bailu Si, Klaus Pawelzik, J. Michael Herrmann:
Robot Exploration by Subjectively Maximizing Objective Information Gain. ROBIO 2004: 930-935 - 2003
- [j14]Norbert Michael Mayer, J. Michael Herrmann, Theo Geisel:
Shaping of Receptive Fields in the Visual Cortex During Retinal Maturation. J. Comput. Neurosci. 15(3): 307-320 (2003) - 2002
- [j13]Dmitri Bibitchkov, J. Michael Herrmann, Theo Geisel:
Effects of short-time plasticity on the associative memory. Neurocomputing 44-46: 329-335 (2002) - [j12]Norbert Michael Mayer, J. Michael Herrmann, Theo Geisel:
Curved feature metrics in models of visual cortex. Neurocomputing 44-46: 533-539 (2002) - [j11]Silke Dodel, J. Michael Herrmann, Theo Geisel:
Functional connectivity by cross-correlation clustering. Neurocomputing 44-46: 1065-1070 (2002) - 2001
- [j10]Norbert Michael Mayer, J. Michael Herrmann, Theo Geisel:
Signatures of natural image statistics in cortical simple cell receptive fields. Neurocomputing 38-40: 279-284 (2001) - [j9]J. Michael Herrmann:
Dynamical systems for predictive control of autonomous robots. Theory Biosci. 120(3-4): 241-252 (2001) - [c8]Silke Dodel, J. Michael Herrmann, Theo Geisel:
Stimulus-Independent Data Analysis for fMRI. Emergent Neural Computational Architectures Based on Neuroscience 2001: 39-53 - 2000
- [j8]Norbert Michael Mayer, J. Michael Herrmann, Theo Geisel:
Retinotopy and spatial phase in topographic maps. Neurocomputing 32-33: 447-452 (2000) - [j7]Silke Dodel, J. Michael Herrmann, Theo Geisel:
Localization of brain activity - blind separation for fMRI data. Neurocomputing 32-33: 701-708 (2000) - [j6]J. Michael Herrmann, Klaus Pawelzik, Theo Geisel:
Learning predictive representations. Neurocomputing 32-33: 785-791 (2000) - [c7]Dmitri Bibitchkov, J. Michael Herrmann, Theo Geisel:
Synaptic Depression in Associative Memory Networks. IJCNN (5) 2000: 50-58 - [c6]Norbert Michael Mayer, J. Michael Herrmann, Theo Geisel:
Structure Formation in Visual Cortex Based on a Curved Feature Space. IJCNN (6) 2000: 153-158
1990 – 1999
- 1999
- [j5]J. Michael Herrmann, Klaus Pawelzik, Theo Geisel:
Self-Localization of Autonomous Robots by Hidden Representations. Auton. Robots 7(1): 31-40 (1999) - [j4]J. Michael Herrmann, Klaus Pawelzik:
Simultaneous self-organization of place and direction selectivity in a neural model of self-localization. Neurocomputing 26-27: 721-727 (1999) - [j3]Hans-Ulrich Bauer, J. Michael Herrmann, Thomas Villmann:
Neural maps and topographic vector quantization. Neural Networks 12(4-5): 659-676 (1999) - 1998
- [c5]Thomas Villmann, J. Michael Herrmann:
Magnification control in neural maps. ESANN 1998: 191-196 - 1997
- [j2]Ralf Der, J. Michael Herrmann, Thomas Villmann:
Time behavior of topological ordering in self-organizing feature mapping. Biol. Cybern. 77(6): 419-427 (1997) - [j1]Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz:
Topology preservation in self-organizing feature maps: exact definition and measurement. IEEE Trans. Neural Networks 8(2): 256-266 (1997) - [c4]J. Michael Herrmann, Hans-Ulrich Bauer, Thomas Villmann:
Measuring topology preservation in maps of real-world data. ESANN 1997 - [c3]J. Michael Herrmann, Thomas Villmann:
Vector Quantization by Optimal Neural Gas. ICANN 1997: 625-630 - 1994
- [c2]Ralf Der, J. Michael Herrmann:
Instabilities in self-organized feature maps with short neighbourhood range. ESANN 1994 - [c1]Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz:
Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement. Fuzzy Days 1994: 159-166
Coauthor Index
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