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Martin Stetter
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2020 – today
- 2021
- [j21]Martin Stetter
, Elmar Wolfgang Lang
Learning Intuitive Physics and One-Shot Imitation Using State-Action-Prediction Self-Organizing Maps. Comput. Intell. Neurosci. 2021: 5590445:1-5590445:15 (2021) - 2020
- [i1]Martin Stetter, Elmar Wolfgang Lang:
Learning intuitive physics and one-shot imitation using state-action-prediction self-organizing maps. CoRR abs/2007.01647 (2020)
2010 – 2019
- 2014
- [j20]Torsten Schön, Martin Stetter, Ana Maria Tomé
Physarum Learner: A bio-inspired way of learning structure from data. Expert Syst. Appl. 41(11): 5353-5370 (2014) - 2013
- [c15]Torsten Schön, Martin Stetter, Ana Maria Tomé, Elmar Wolfgang Lang:
A New Physarum Learner for Network Structure Learning from Biomedical Data. BIOSIGNALS 2013: 151-156 - 2012
- [c14]Torsten Schön, Martin Stetter, Elmar Wolfgang Lang:
Structure Learning for Bayesian Networks Using the Physarum Solver. ICMLA (1) 2012: 488-493
2000 – 2009
- 2008
- [j19]Reinhard Schachtner, Dominik Lutter
Knowledge-based gene expression classification via matrix factorization. Bioinform. 24(15): 1688-1697 (2008) - [j18]Markus Bundschus, Mathäus Dejori, Martin Stetter, Volker Tresp, Hans-Peter Kriegel:
Extraction of semantic biomedical relations from text using conditional random fields. BMC Bioinform. 9 (2008) - [j17]Rui Chang, Wilfried Brauer, Martin Stetter:
Modeling semantics of inconsistent qualitative knowledge for quantitative Bayesian network inference. Neural Networks 21(2-3): 182-192 (2008) - [j16]Rui Chang, Martin Stetter, Wilfried Brauer:
Quantitative Inference by Qualitative Semantic Knowledge Mining with Bayesian Model Averaging. IEEE Trans. Knowl. Data Eng. 20(12): 1587-1600 (2008) - 2007
- [c13]Rui Chang, Martin Stetter:
A Knowledge-based Dynamic Bayesian Framework Towards Molecular Network Modeling and Quantitative Prediction. BIOCOMP 2007: 37-43 - [c12]Andreas Nägele, Mathäus Dejori, Martin Stetter:
Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures. ECML 2007: 238-249 - [c11]Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter:
Structure Learning with Nonparametric Decomposable Models. ICANN (1) 2007: 119-128 - [c10]Rui Chang, Martin Stetter:
Quantitative Bayesian Inference by Qualitative Knowledge Modeling. IJCNN 2007: 2563-2568 - 2006
- [j15]Miruna Szabo, Martin Stetter, Gustavo Deco, Stefano Fusi
Learning to Attend: Modeling the Shaping of Selectivity in Infero-temporal Cortex in a Categorization Task. Biol. Cybern. 94(5): 351-365 (2006) - [c9]Martin Stetter, Bernd Schürmann, Michael Hofstetter:
Logical nano-computation in enzymatic reaction networks. BIONETICS 2006: 7 - 2005
- [j14]Miruna Szabo, Rita Almeida
A neuronal model for the shaping of feature selectivity in IT by visual categorization. Neurocomputing 65-66: 195-201 (2005) - [j13]Janaina Mourão Miranda, Arun L. W. Bokde, Christine Born, Harald Hampel, Martin Stetter:
Classifying brain states and determining the discriminating activation patterns: Support Vector Machine on functional MRI data. NeuroImage 28(4): 980-995 (2005) - 2004
- [j12]Martin Stetter, Elmar Wolfgang Lang:
Modeling texture-constancy of cortical grating cells. Neurocomputing 58-60: 835-841 (2004) - [j11]Mathäus Dejori, Martin Stetter:
Identifying Interventional and Pathogenic Mechanisms by Generative Inverse Modeling of Gene Expression Profiles. J. Comput. Biol. 11(6): 1135-1148 (2004) - [p2]Martin Stetter, Bernd Schürmann, Mathäus Dejori:
Systems Level Modeling of Gene Regulatory Networks. Artificial Intelligence Methods And Tools For Systems Biology 2004: 175-195 - [p1]Marco Loh, Miruna Szabo, Rita Almeida, Martin Stetter, Gustavo Deco:
Computational Neuroscience for Cognitive Brain Functions. Artificial Intelligence Methods And Tools For Systems Biology 2004: 197-215 - 2003
- [j10]Martin Stetter, Gustavo Deco, Mathäus Dejori:
Large-Scale Computational Modeling of Genetic Regulatory Networks. Artif. Intell. Rev. 20(1-2): 75-93 (2003) - [j9]Silvia Corchs
Systems-Level Neuronal Modeling of Visual Attentional Mechanisms. Artif. Intell. Rev. 20(1-2): 143-160 (2003) - [c8]Mathäus Dejori, Martin Stetter:
Bayesian Inference of Genetic Networks from Gene-Expression-Data: Convergence and Reliability. IC-AI 2003: 323-327 - 2002
- [j8]Rita Almeida
Modeling the Link between Functional Imaging and Neuronal Activity: Synaptic Metabolic Demand and Spike Rates. NeuroImage 17(2): 1065-1079 (2002) - 2001
- [j7]Hauke Bartsch
Contextual effects by short range connections in a mean-field model of V1. Neurocomputing 38-40: 475-481 (2001) - [c7]Hauke Bartsch, Martin Stetter, Klaus Obermayer:
On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex. Emergent Neural Computational Architectures Based on Neuroscience 2001: 174-187 - 2000
- [j6]Martin Stetter, Hauke Bartsch
A mean-field model for orientation tuning, contrast saturation, and contextual effects in the primary visual cortex. Biol. Cybern. 82(4): 291-304 (2000) - [j5]Hauke Bartsch
The influence of threshold variability on the response of visual cortical neurons. Neurocomputing 32-33: 37-43 (2000) - [j4]T. Müller, Martin Stetter, Mark Hübener, Frank Sengpiel, Tobias Bonhoeffer, I. Gödecke, Barbara Chapman, Siegrid Löwel, Klaus Obermayer:
An Analysis of Orientation and Ocular Dominance Patterns in the Visual Cortex of Cats and Ferrets. Neural Comput. 12(11): 2573-2595 (2000) - [j3]Ingo Schießl
Blind signal separation from optical imaging recordings with extended spatial decorrelation. IEEE Trans. Biomed. Eng. 47(5): 573-577 (2000) - [c6]Ingo Schießl
Blind Signal Separation from Optical Imaging Data. DAGM-Symposium 2000: 91-98
1990 – 1999
- 1999
- [c5]Holger Schoner, Martin Stetter, Ingo Schießl, John E. W. Mayhew, Jennifer S. Lund, Niall McLoughlin, Klaus Obermayer:
Application of Blind Separation of Sources to Optical Recording of Brain Activity. NIPS 1999: 949-955 - 1998
- [j2]K. Brunner, M. Kussinger, Martin Stetter, Elmar Wolfgang Lang:
A neural network model for the emergence of grating cells. Biol. Cybern. 78(5): 389-397 (1998) - [c4]Martin Stetter, Péter Adorján, Hauke Bartsch, Klaus Obermayer:
Modelling Contrast Adaptation and Contextual Effects in Primary Visual Cortex. ICONIP 1998: 669-672 - 1997
- [c3]Martin Stetter, Elmar Wolfgang Lang, Klaus Obermayer:
Synapse Clustering Can Drive Simultaneous ON-OFF and Ocular-Dominance Segregation in a Model of Area 17. ICANN 1997: 189-194 - [c2]Hauke Bartsch, Martin Stetter, Klaus Obermayer:
A Model for Orientation Tuning and Contextual Effects of Orientation Selective Receptive Fields. ICANN 1997: 237-242 - 1995
- [c1]Martin Stetter, M. Kussinger, Armin Schels, E. Seeger, Elmar Wolfgang Lang:
Self-Organization of Cortical Receptive Fields and Columnar Structures in a Hebb Trained Neural Network. IWANN 1995: 37-44 - 1994
- [b1]Martin Stetter:
Selbstorganisation funktioneller Strukturen im primären visuellen Kortex: ein neuronales Netzwerk als Modell aktivitätsabhängiger Reifungsprozesse. University of Regensburg, Germany, Roderer 1994, ISBN 978-3-89073-720-1, pp. 1-171 - 1993
- [j1]Martin Stetter, Elmar Wolfgang Lang, A. Müller:
Emergence of orientation selective simple cells simulated in deterministic and stochastic neural networks. Biol. Cybern. 68(5): 465-476 (1993)
Coauthor Index
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