2017


T. Nguyen, W. Liu, F. Sinz, R. G. Baraniuk, A. S. Tolias, X. Pitkow, and A. B. Patel
Towards a Cortically Inspired Deep Learning Model: Semi-Supervised Learning, Divisive Normalization, and Synaptic Pruning
Cognitive Computational Neuroscience (CNN 2017), 2017
PDF, BibTex
F. H. Sinz, C. Sachgau, J. Henninger, J. Benda, and J. Grewe
Simultaneous spike-time locking to multiple frequencies
biorxiv, 2017
Code, URL, docker, BibTex
M. Ren, R. Liao, R. Urtasun, F. H. Sinz, and R. S. Zemel
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes
ICLR 2017, 2017
arXiv link, BibTex

2016


Hartmann, L., Drewe-Boß, P., Wießner, T., Wagner, G., et al.
Alternative Splicing Substantially Diversifies the Transcriptome during Early Photomorphogenesis and Correlates with the Energy Availability in Arabidopsis
The Plant Cell (in press), 2016
BibTex
X. Jiang, S. Shen, F. Sinz, J. Reimer, C. R. Cadwell, P. Berens, A. S. Ecker, S. Patel, et al.
Response to Comment on “Principles of connectivity among morphologically defined cell types in adult neocortex”
Science, 353(6304), 1108, 2016
Code, URL, Docker, BibTex

2015


X. Jiang, S. Shen, C. R. Cadwell, P. Berens, F. Sinz, A. S. Ecker, S. Patel, and A. S. Tolias
Principles of connectivity among morphologically defined cell types in adult neocortex
Science, 350(6264), 2015
Code, URL, DOI, BibTex
D. Yatsenko, J. Reimer, A. S. Ecker, E. Y. Walker, F. Sinz, P. Berens, A. Hoenselaar, R. J. Cotton, et al.
DataJoint: managing big scientifc data using MATLAB or Pythonn
2015
Code, PDF, BibTex

2014


A. Stöckl, F. Sinz, J. Benda, and J. Grewe
Encoding of social signals in all three electrosensory pathways of Eigenmannia virescens
Journal of Neurophysiology (accepted), 2014
Code, DOI, PDF, BibTex
E. Froudarakis, P. Berens, A. Ecker, J. R. 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
URL, DOI, BibTex
F. Sinz, P. Lies, S. Gerwinn, and M. Bethge
Natter: A Python Natural Image Statistics Toolbox
Journal of Statistical Software (accepted), 2014
BibTex

2013


F. Sinz and M. Bethge
What is the Limit of Redundancy Reduction with Divisive Normalization?
Neural Computation, 25, 2809-2814, 2013
Code, URL, DOI, BibTex
F. Sinz, A. Stöckl, J. Grewe, and J. Benda
Least Informative Dimensions
Advances in Neural Information Processing Systems, 2013
Code, PDF, Poster, Errata, BibTex
F. Sinz and M. Bethge
Temporal Adaptation Enhances Efficient Contrast Gain Control on Natural Images
PLoS Comput Biol, 9(1), 2013
URL, DOI, Poster, BibTex

2012


F. Sinz
Orientation Selectivity and Contrast Gain Control in Representations of Natural Images
PhD Thesis, Graduate School of Neural and Behavioural Sciences, University Tuebingen, 2012
PDF, BibTex

2011


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
Code, URL, BibTex

2010


F. Sinz and M. Bethge
Lp-nested symmetric distributions
Journal of Machine Learning Research, 3409-3451, 2010
#natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions
PDF, BibTex
R. Hosseini, F. Sinz, and M. Bethge
Lower bounds on the redundancy of natural images
Vision Research, 2213-2222, 2010
#natural image statistics
PDF, BibTex

2009


J. Eichhorn, F. Sinz, and M. Bethge
Natural Image Coding in V1: How Much Use Is Orientation Selectivity?
PLoS Computational Biology, 5(4), 2009
#natural image models, #natural image statistics, #normative models
Code, 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, BibTex
F. H. Sinz, E. Simoncelli, and M. Bethge
Hierarchical Modeling of Local Image Features through Lp-Nested Symmetric Distributions
Advances in Neural Information Processing Systems 22, 2009
#natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions
PDF, BibTex

2008


F. Sinz and M. Bethge
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
Advances in Neural Information Processing Systems 21, 2008
#contrast gain control, #normative models, #natural image statistics, #lp-spherically symmetric distributions
PDF, BibTex
F. H. Sinz and M. Bethge
How much can orientation selectivity and contrast gain control reduce the redundancies in natural images
Max Planck Institute for Biological Cybernetics Technical Report 169, 2008
#natural image models, #natural image statistics, #normative models, #ica
PDF, BibTex

2007


F. Sinz
A priori knowledge from non-examples
Diploma Thesis, 2007
PDF, BibTex
F. H. Sinz, O. Chapelle, A. Agarwal, and B. Schölkopf
An Analysis of Inference with the Universum
Advances in Neural Information Processing Systems 20, 2007
PDF, Poster, BibTex

2006


F. H. Sinz and B. Schölkopf
Minimal Logical Constraint Covering Sets
Max Planck Institute for Biological Cybernetics Technical Report 155, 2006
#linear programming, #logical constraints, #covering set
PDF, BibTex
J. Weston, R. Collobert, F. Sinz, L. Bottou, and V. Vapnik
Inference with the Universum
Proceedings of the 23rd international conference on Machine learning ICML 06, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, Poster, BibTex
J. Quinonero-Candela, C. E. Rasmussen, F. Sinz, and B. Schoelkopf
Evaluating Predictive Uncertainty Challenge
Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... Computer Science / Lecture Notes in Artific), 2006
#machine learning challenge, #predictive uncertainty
BibTex
R. Collobert, F. Sinz, J. Weston, and L. Bottou
Trading Convexity for Scalability
Proceedings of the 23rd international conference on Machine learning ICML 06, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, Errata, BibTex
R. Collobert, F. Sinz, J. Weston, and L. Bottou
Large scale transductive SVMs
Journal of Machine Learning Research, 7, 1687-1712, 2006
#cccp optimization, #svms, #semi-supervised learning, #transductive learning
URL, DOI, PDF, BibTex

2004


F. Sinz
Kamerakalibrierung und Tiefenschätzung Ein Vergleich von klassischer Bündelblockausgleichung und statistischen Lernalgorithmen
Student Research Project, 2004
PDF, BibTex
F. Sinz, G. Quinonero-Candela, G. Bakir, C. Rassmussen, and M. Franz
Learning Depth From Stereo
Pattern Recognition Proc 26th DAGM Symposium LNCS 3175, 2004
#camera calibration, #machine learning
PDF, BibTex
D. Goeruer, C. E. Rasmussen, A. S. Tolias, F. Sinz, and N. K. Logothetis
Modelling Spikes with Mixtures of Factor Analysers
Pattern Recognition Proc 26th DAGM Symposium LNCS 3175, 2004
#spike sorting, #clustering, #mixture of factor analyzers
URL, PDF, BibTex