2014


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
M. Kümmerer, T. Wallis, and M. Bethge
How close are we to understanding image-based saliency?
arXiv, 2014
#saliency
URL, BibTex
H. E. Gerhard and M. Bethge
Towards rigorous study of artistic style: a new psychophysical paradigm
Art and Perception, 2, 23-44, 2014
#psychophysics, #texture discrimination, #stylometry
Code, URL, DOI, PDF, BibTex
A. S. Ecker and A. S. Tolias
Is there signal in the noise?
Nature Neuroscience, 17, 750-751, 2014
#variability, #modulated poisson, #noise correlations
URL, DOI, BibTex
E. Froudarakis, P. Berens, A. S. Ecker, R. J. Cotton, F. H. Sinz, D. Yatsenko, P. Saggau, M. Bethge, et al.
Population code in mouse V1 facilitates read-out of natural scenes through increased sparseness
Nature Neuroscience, 17, 851-857, 2014
#sparsity, #natural image statistics, #population coding, #v1, #two-photon imaging
URL, DOI, PDF, BibTex
M. Bethge
Efficient Population Coding
Encyclopedia of Computational Neuroscience, Springer New York, 2014
#population coding
URL, DOI, PDF, BibTex
A. S. Ecker, P. Berens, R. J. Cotton, M. Subramaniyan, G. H. Denfield, C. R. Cadwell, S. M. Smirnakis, M. Bethge, et al.
State dependence of noise correlations in macaque primary visual cortex
Neuron, 82(1), 235-248, 2014
#noise correlations, #gpfa, #population, #anesthesia, #macaque
Code, URL, DOI, PDF, BibTex
J.-P. Lies, R. M. Häfner, and M. Bethge
Slowness and sparseness have diverging effects on complex cell learning
PLoS Computational Biology, 10(3), 2014
#slowness, #sparsity, #complex cell, #natural image statistics, #unsupervised learning
Code, URL, DOI, PDF, BibTex
University of Tuebingen BCCN CIN MPI