Publications by S. Gerwinn

Journal Articles


F. Sinz, J.-P. Lies, S. Gerwinn, and M. Bethge
Natter: A Python Natural Image Statistics Toolbox
Journal of Statistical Software, 61(5), 2014
#natural image statistics, #software, #python
Code, PDF, BibTex
R. M. Haefner, S. Gerwinn, J. H. Macke, and M. Bethge
Inferring decoding strategies from choice probabilities in the presence of correlated variability
Nature Neuroscience, 16, 235-242, 2013
#noise correlations, #choice probabilities, #decision making, #population coding
Code, URL, PDF, Perspective, BibTex
L. Theis, S. Gerwinn, F. Sinz, and M. Bethge
In All Likelihood, Deep Belief Is Not Enough
Journal of Machine Learning Research, 12, 3071-3096, 2011
#natural image statistics, #deep belief networks, #boltzmann machines, #deep learning
Code, PDF, BibTex
P. Berens, A. S. Ecker, S. Gerwinn, A. S. Tolias, and M. Bethge
Reassessing optimal neural population codes with neurometric functions
Proceedings of the National Academy of Sciences of the United States of America, 108(11), 4423-4428, 2011
#fisher information, #population coding, #mean squared error, #discrimination error, #neurometric function
Code, URL, PDF, BibTex
S. Gerwinn, J. Macke, and M. Bethge
Reconstructing stimuli from the spike times of leaky integrate and fire neurons
Frontiers in Neuroscience, 5, 2011
#population coding, #decoding, #bayesian inference, #spiking neurons
URL, DOI, PDF, BibTex
S. Gerwinn, J. Macke, and M. Bethge
Bayesian inference for generalized linear models for spiking neurons
Frontiers in Computational Neuroscience, 4, 2010
#bayesian inference, #generalized linear model, #spiking neurons
Code, URL, DOI, PDF, BibTex
J. H. Macke, S. Gerwinn, L. White, M. Kaschube, and M. Bethge
Gaussian process methods for estimating cortical maps
NeuroImage, 56(2), 570-581, 2010
#gaussian process
Code, URL, DOI, PDF, BibTex
S. Gerwinn, J. Macke, and M. Bethge
Bayesian population decoding of spiking neurons
Frontiers in Computational Neuroscience, 3, 2009
#population coding, #decoding
URL, DOI, PDF, BibTex
F. H. Sinz, S. Gerwinn, and M. Bethge
Characterization of the p-Generalized Normal Distribution
Journal of Multivariate Analysis, 100(5), 817-820, 2009
#p-generalized normal distribution, #uniqueness theorem, #power exponential distribution
URL, DOI, PDF, BibTex
M. Seeger, S. Gerwinn, and M. Bethge
Bayesian Inference for Sparse Generalized Linear Models
Lecture Notes in Computer Science, 2007
BibTex

Conference Papers


J. H. Macke, S. Gerwinn, M. Kaschube, L. E. White, and M. Bethge
Bayesian estimation of orientation preference maps
Advances in Neural Information Processing Systems 22, 2009
#bayesian inference, #orientation maps
Code, PDF, BibTex
S. Gerwinn, P. Berens, and M. Bethge
A joint maximum-entropy model for binary neural population patterns and continuous signals
Advances in Neural Information Processing Systems 22, 2009
#maximum entropy, #population coding
Code, PDF, BibTex
P. Berens, S. Gerwinn, A. S. Ecker, and M. Bethge
Neurometric function analysis of population codes
Advances in Neural Information Processing Systems 22, 2009
#population coding, #neurometric function
Code, PDF, BibTex
S. Gerwinn, J. Macke, M. Seeger, and M. Bethge
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Advances in Neural Information Processing Systems 20, 2008
PDF, BibTex
M. Bethge, S. Gerwinn, and J. H. Macke
Unsupervised learning of a steerable basis for invariant image representations
Proceedings of SPIE Human Vision and Electronic Imaging XII (EI105), 2007
PDF, BibTex

Abstracts


L. Theis, S. Gerwinn, F. Sinz, and M. Bethge
Likelihood Estimation in Deep Belief Networks
Frontiers in Computational Neuroscience, 2010
#deep belief networks, #likelihood estimation, #natural image statistics
Code, URL, DOI, BibTex
S. Gerwinn, M. Seeger, G. Zeck, and M. Bethge
Bayesian Neural System identification: error bars, receptive fields and neural couplings
Proceedings of the 31st Göttingen Neurobiology Conference, 2007
#bayesian inference, #receptive fields
PDF, BibTex
M. Bethge, J. H. Macke, S. Gerwinn, and G. Zeck
Identifying temporal population codes in the retina using canonical correlation analysis
Proceedings of the 31st Göttingen Neurobiology Conference, 2007
BibTex
University of Tuebingen BCCN CIN MPI