Emergence of orientation selective simple cells simulated in deterministic and stochastic neural networks. - Martin Stetter; Elmar Wolfgang Lang; A. Müller (Biol. Cybern., 1993)

Selbstorganisation funktioneller Strukturen im primären visuellen Kortex: ein neuronales Netzwerk als Modell aktivitätsabhängiger Reifungsprozesse. - Martin Stetter (Roderer, 1994)

Self-Organization of Cortical Receptive Fields and Columnar Structures in a Hebb Trained Neural Network. - Martin Stetter; M. Kussinger; Armin Schels; E. Seeger; Elmar Wolfgang Lang (IWANN, 1995)

A Model for Orientation Tuning and Contextual Effects of Orientation Selective Receptive Fields. - Hauke Bartsch; Martin Stetter; Klaus Obermayer (ICANN, 1997)

Synapse Clustering Can Drive Simultaneous ON-OFF and Ocular-Dominance Segregation in a Model of Area 17. - Martin Stetter; Elmar Wolfgang Lang; Klaus Obermayer (ICANN, 1997)

Modelling Contrast Adaptation and Contextual Effects in Primary Visual Cortex. - Martin Stetter; Péter Adorján; Hauke Bartsch; Klaus Obermayer (ICONIP, 1998)

A neural network model for the emergence of grating cells. - K. Brunner; M. Kussinger; Martin Stetter; Elmar Wolfgang Lang (Biol. Cybern., 1998)

Application of Blind Separation of Sources to Optical Recording of Brain Activity. - Holger Schoner; Martin Stetter; Ingo Schießl; John E. W. Mayhew; Jennifer S. Lund; Niall McLoughlin; Klaus Obermayer (NIPS, 1999)

Blind Signal Separation from Optical Imaging Data. - Ingo Schießl; Martin Stetter; John E. W. Mayhew; Niall McLoughlin; Jennifer S. Lund; Klaus Obermayer (DAGM-Symposium, 2000)

A mean-field model for orientation tuning, contrast saturation, and contextual effects in the primary visual cortex. - Martin Stetter; Hauke Bartsch; Klaus Obermayer (Biol. Cybern., 2000)

The influence of threshold variability on the response of visual cortical neurons. - Hauke Bartsch; Martin Stetter; Klaus Obermayer (Neurocomputing, 2000)

An Analysis of Orientation and Ocular Dominance Patterns in the Visual Cortex of Cats and Ferrets. - T. Müller; Martin Stetter; Mark Hübener; Frank Sengpiel; Tobias Bonhoeffer; I. Gödecke; Barbara Chapman 001; Siegrid Löwel; Klaus Obermayer (Neural Comput., 2000)

Blind signal separation from optical imaging recordings with extended spatial decorrelation. - Ingo Schießl; Martin Stetter; John E. W. Mayhew; Niall McLoughlin; Jennifer S. Lund; Klaus Obermayer (IEEE Trans. Biomed. Eng., 2000)

On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex. - Hauke Bartsch; Martin Stetter; Klaus Obermayer (Emergent Neural Computational Architectures Based on Neuroscience, 2001)

Contextual effects by short range connections in a mean-field model of V1. - Hauke Bartsch; Martin Stetter; Klaus Obermayer (Neurocomputing, 2001)

Modeling the Link between Functional Imaging and Neuronal Activity: Synaptic Metabolic Demand and Spike Rates. - Rita Almeida; Martin Stetter (NeuroImage, 2002)

Bayesian Inference of Genetic Networks from Gene-Expression-Data: Convergence and Reliability. - Mathäus Dejori; Martin Stetter (IC-AI, 2003)

Systems-Level Neuronal Modeling of Visual Attentional Mechanisms. - Silvia Corchs; Martin Stetter; Gustavo Deco (Artif. Intell. Rev., 2003)

Large-Scale Computational Modeling of Genetic Regulatory Networks. - Martin Stetter; Gustavo Deco; Mathäus Dejori (Artif. Intell. Rev., 2003)

Modeling texture-constancy of cortical grating cells. - Martin Stetter; Elmar Wolfgang Lang (Neurocomputing, 2004)

Identifying Interventional and Pathogenic Mechanisms by Generative Inverse Modeling of Gene Expression Profiles. - Mathäus Dejori; Martin Stetter (J. Comput. Biol., 2004)

Computational Neuroscience for Cognitive Brain Functions. - Marco Loh; Miruna Szabo; Rita Almeida; Martin Stetter; Gustavo Deco (Artificial Intelligence Methods And Tools For Systems Biology, 2004)

Systems Level Modeling of Gene Regulatory Networks. - Martin Stetter; Bernd Schürmann; Mathäus Dejori (Artificial Intelligence Methods And Tools For Systems Biology, 2004)

A neuronal model for the shaping of feature selectivity in IT by visual categorization. - Miruna Szabo; Rita Almeida; Gustavo Deco; Martin Stetter (Neurocomputing, 2005)

Classifying brain states and determining the discriminating activation patterns: Support Vector Machine on functional MRI data. - Janaina Mourão Miranda; Arun L. W. Bokde; Christine Born; Harald Hampel; Martin Stetter (NeuroImage, 2005)

Logical nano-computation in enzymatic reaction networks. - Martin Stetter; Bernd Schürmann; Michael Hofstetter (BIONETICS, 2006)

Learning to Attend: Modeling the Shaping of Selectivity in Infero-temporal Cortex in a Categorization Task. - Miruna Szabo; Martin Stetter; Gustavo Deco; Stefano Fusi; Paolo Del Giudice; Maurizio Mattia (Biol. Cybern., 2006)

A Knowledge-based Dynamic Bayesian Framework Towards Molecular Network Modeling and Quantitative Prediction. - Rui Chang; Martin Stetter (BIOCOMP, 2007)

Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures. - Andreas Nägele; Mathäus Dejori; Martin Stetter (ECML, 2007)

Structure Learning with Nonparametric Decomposable Models. - Anton Schwaighofer; Mathäus Dejori; Volker Tresp; Martin Stetter (ICANN (1), 2007)

Quantitative Bayesian Inference by Qualitative Knowledge Modeling. - Rui Chang; Martin Stetter (IJCNN, 2007)

Knowledge-based gene expression classification via matrix factorization. - Reinhard Schachtner; Dominik Lutter; P. Knollmüller; Ana Maria Tomé; Fabian J. Theis; Gerd Schmitz 001; Martin Stetter; Pedro Gómez-Vilda; Elmar Wolfgang Lang (Bioinform., 2008)

Extraction of semantic biomedical relations from text using conditional random fields. - Markus Bundschus; Mathäus Dejori; Martin Stetter; Volker Tresp; Hans-Peter Kriegel (BMC Bioinform., 2008)

Modeling semantics of inconsistent qualitative knowledge for quantitative Bayesian network inference. - Rui Chang; Wilfried Brauer; Martin Stetter (Neural Networks, 2008)

Quantitative Inference by Qualitative Semantic Knowledge Mining with Bayesian Model Averaging. - Rui Chang; Martin Stetter; Wilfried Brauer (IEEE Trans. Knowl. Data Eng., 2008)

Structure Learning for Bayesian Networks Using the Physarum Solver. - Torsten Schön; Martin Stetter; Elmar Wolfgang Lang (ICMLA (1), 2012)

A New Physarum Learner for Network Structure Learning from Biomedical Data. - Torsten Schön; Martin Stetter; Ana Maria Tomé; Elmar Wolfgang Lang (BIOSIGNALS, 2013)

Physarum Learner: A bio-inspired way of learning structure from data. - Torsten Schön; Martin Stetter; Ana Maria Tomé; Carlos García Puntonet; Elmar Wolfgang Lang (Expert Syst. Appl., 2014)

Learning Intuitive Physics and One-Shot Imitation Using State-Action-Prediction Self-Organizing Maps. - Martin Stetter; Elmar Wolfgang Lang (Comput. Intell. Neurosci., 2021)