Publications by F. Sinz
Preprints
S. A. Cadena,
K. F. Willeke,
K. Restivo,
G. Denfield,
F. H. Sinz,
M. Bethge,
A. S. Tolias, and
A. S. Ecker
Diverse task-driven modeling of macaque V4 reveals functional specialization towards semantic tasks
BioRxiv, 2022
URL, DOI, URL, PDF, BibTex
Diverse task-driven modeling of macaque V4 reveals functional specialization towards semantic tasks
BioRxiv, 2022
URL, DOI, URL, PDF, BibTex
S. Safarani,
A. Nix,
K. Willeke,
S. A. Cadena,
K. Restivo,
G. Denfield,
A. S. Tolias, and
F. H. Sinz
Towards robust vision by multi-task learning on monkey visual cortex
arXiv preprint arXiv:2107.14344, 2021
BibTex
Towards robust vision by multi-task learning on monkey visual cortex
arXiv preprint arXiv:2107.14344, 2021
BibTex
Journal Articles
E. Y. Walker,
F. H. Sinz,
E. Froudarakis,
P. G. Fahey,
T. Muhammad,
A. S. Ecker,
E. Cobos,
J. Reimer,
et al.
Inception loops discover what excites neurons most using deep predictive models
Nature Neuroscience, 2019
#primary visual cortex, #deep neural network, #system identification, #inception
URL, DOI, BibTex
Inception loops discover what excites neurons most using deep predictive models
Nature Neuroscience, 2019
#primary visual cortex, #deep neural network, #system identification, #inception
URL, DOI, BibTex
X. Jiang,
S. Shen,
C. Cadwell,
P. Berens,
F. Sinz,
A. S. Ecker,
S. Patel, and
A. Tolias
Principles of connectivity among morphologically defined cell types in adult neocortex
Science, 350(6264), 1055, 2015
#connectivity, #interneurons, #morphology, #machine learning
URL, PDF, BibTex
Principles of connectivity among morphologically defined cell types in adult neocortex
Science, 350(6264), 1055, 2015
#connectivity, #interneurons, #morphology, #machine learning
URL, PDF, BibTex
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
Natter: A Python Natural Image Statistics Toolbox
Journal of Statistical Software, 61(5), 2014
#natural image statistics, #software, #python
Code, PDF, 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
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
F. Sinz and
M. Bethge
What is the Limit of Redundancy Reduction with Divisive Normalization?
Neural Computation, 2013
URL, PDF, BibTex
What is the Limit of Redundancy Reduction with Divisive Normalization?
Neural Computation, 2013
URL, PDF, BibTex
F. Sinz and
M. Bethge
Temporal adaptation enhances efficient contrast gain control on natural images
PLoS Computational Biology, 9(1), 2013
#natural image statistics, #divisive normalization, #contrast gain control, #lp-spherically symmetric distributions
Code, URL, PDF, BibTex
Temporal adaptation enhances efficient contrast gain control on natural images
PLoS Computational Biology, 9(1), 2013
#natural image statistics, #divisive normalization, #contrast gain control, #lp-spherically symmetric distributions
Code, URL, PDF, 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
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
F. Sinz and
M. Bethge
Lp-nested symmetric distributions
Journal of Machine Learning Research, 11, 3409-3451, 2010
#natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions
PDF, BibTex
Lp-nested symmetric distributions
Journal of Machine Learning Research, 11, 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, 50(22), 2213-2222, 2010
#natural image statistics
PDF, BibTex
Lower bounds on the redundancy of natural images
Vision Research, 50(22), 2213-2222, 2010
#natural image statistics
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
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
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, DOI, PDF, BibTex
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, DOI, PDF, 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
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
Conference Papers
I. Ustyuzhaninov,
S. A. Cadena,
E. Froudarakis,
P. G. Fahey,
E. Y. Walker,
E. Cobos,
J. Reimer,
F. H. Sinz,
et al.
Rotation-invariant clustering of functional cell types in primary visual cortex
International Conference on Learning Representations (ICLR), 2020
URL, PDF, BibTex
Rotation-invariant clustering of functional cell types in primary visual cortex
International Conference on Learning Representations (ICLR), 2020
URL, PDF, BibTex
A. S. Ecker,
F. H. Sinz,
E. Froudarakis,
P. G. Fahey,
S. A. Cadena,
E. Y. Walker,
E. Cobos,
J. Reimer,
et al.
A rotation-equivariant convolutional neural network model of primary visual cortex
International Conference on Learning Representations (ICLR), 2019
#v1, #system identification, #microns, #convolutional neural network, #rotation equivariance
Code, URL, PDF, Data, BibTex
A rotation-equivariant convolutional neural network model of primary visual cortex
International Conference on Learning Representations (ICLR), 2019
#v1, #system identification, #microns, #convolutional neural network, #rotation equivariance
Code, URL, PDF, Data, BibTex
S. A. Cadena,
F. H. Sinz,
T. Muhammad,
E. Froudarakis,
E. Cobos,
E. Y. Walker,
J. Reimer,
M. Bethge,
et al.
How well do deep neural networks trained on object recognition characterize the mouse visual system?
NeurIPS Neuro AI Workshop, 2019
#mouse visual cortex, #goal-driven modeling, #object recognition, #deep neural networks, #hierarchical organization
URL, PDF, BibTex
How well do deep neural networks trained on object recognition characterize the mouse visual system?
NeurIPS Neuro AI Workshop, 2019
#mouse visual cortex, #goal-driven modeling, #object recognition, #deep neural networks, #hierarchical organization
URL, PDF, BibTex
F. H. Sinz,
A. S. Ecker,
P. G. Fahey,
E. Y. Walker,
E. Cobos,
E. Froudarakis,
D. Yatsenko,
X. Pitkow,
et al.
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Advances in Neural Information Processing Systems 32, 2018
#v1, #system identification, #microns, #deep neural network, #recurrent neural network, #domain transfer
URL, PDF, BibTex
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Advances in Neural Information Processing Systems 32, 2018
#v1, #system identification, #microns, #deep neural network, #recurrent neural network, #domain transfer
URL, PDF, 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
Code, PDF, BibTex
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
Code, PDF, BibTex
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
Code, PDF, BibTex
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
Code, 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, 2008
PDF, BibTex
An Analysis of Inference with the Universum
Advances in Neural Information Processing Systems 20, 2008
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, BibTex
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, 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, BibTex
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, 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
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
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
Technical Reports
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, 2008
#natural image models, #natural image statistics, #normative models, #ica, #contrast gain control
PDF, BibTex
How much can orientation selectivity and contrast gain control reduce the redundancies in natural images
Max Planck Institute for Biological Cybernetics, 2008
#natural image models, #natural image statistics, #normative models, #ica, #contrast gain control
PDF, BibTex
F. H. Sinz and
B. Schölkopf
Minimal Logical Constraint Covering Sets
Max Planck Institute for Biological Cybernetics, 2006
#linear programming, #logical constraints, #covering set
PDF, BibTex
Minimal Logical Constraint Covering Sets
Max Planck Institute for Biological Cybernetics, 2006
#linear programming, #logical constraints, #covering set
PDF, BibTex
Book Chapters
J. Quinonero-Candela,
C. E. Rasmussen,
F. Sinz, and
B. Schoelkopf
Evaluating Predictive Uncertainty Challenge
Machine Learning Challenges, Springer, 2006
#machine learning challenge, #predictive uncertainty
URL, BibTex
Evaluating Predictive Uncertainty Challenge
Machine Learning Challenges, Springer, 2006
#machine learning challenge, #predictive uncertainty
URL, BibTex
Abstracts
S. A. Cadena,
K. Willeke,
K. Restivo,
G. Denfield,
E. Y. Walker,
F. Sinz,
M. Bethge,
A. S. Tolias,
et al.
A diverse task-driven characterization of early and mid-level representations of the primate ventral stream
Computational and Systems Neuroscience Meeting (COSYNE 2021), 2021
BibTex
A diverse task-driven characterization of early and mid-level representations of the primate ventral stream
Computational and Systems Neuroscience Meeting (COSYNE 2021), 2021
BibTex
R. Hosseini,
F. Sinz, and
M. Bethge
New Estimate for the Redundancy of Natural Images
Frontiers in Computational Neuroscience, 2010
#natural image statistics, #multi-information rate
DOI, BibTex
New Estimate for the Redundancy of Natural Images
Frontiers in Computational Neuroscience, 2010
#natural image statistics, #multi-information rate
DOI, BibTex
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
Likelihood Estimation in Deep Belief Networks
Frontiers in Computational Neuroscience, 2010
#deep belief networks, #likelihood estimation, #natural image statistics
Code, URL, DOI, BibTex
F. Sinz and
M. Bethge
A new class of distributions for natural images generalizing independent subspace analysis
Frontiers in Computational Neuroscience, 2009
#natural image statistics, #lp-nested symmetric distributions, #independent subspace analysis
DOI, BibTex
A new class of distributions for natural images generalizing independent subspace analysis
Frontiers in Computational Neuroscience, 2009
#natural image statistics, #lp-nested symmetric distributions, #independent subspace analysis
DOI, BibTex
F. Sinz and
M. Bethge
Redundancy Reduction in Natural Images: Quantifying the Effect of Orientation Selectivity and Contrast Gain Control
Gordon Research Conference: Sensory Coding and The Natural Environment, 2008
#natural image statistics, #lp-spherically symmetric distributions, #contrast gain control
BibTex
Redundancy Reduction in Natural Images: Quantifying the Effect of Orientation Selectivity and Contrast Gain Control
Gordon Research Conference: Sensory Coding and The Natural Environment, 2008
#natural image statistics, #lp-spherically symmetric distributions, #contrast gain control
BibTex
F. Sinz and
M. Bethge
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction in Natural Images
Frontiers in Computational Neuroscience, 2008
#natural image statistics, #lp-spherically symmetric distributions, #contrast gain control
DOI, BibTex
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction in Natural Images
Frontiers in Computational Neuroscience, 2008
#natural image statistics, #lp-spherically symmetric distributions, #contrast gain control
DOI, BibTex
F. Sinz and
M. O. Franz
Learning Depth
Proceedings of the 7th Tübingen Perception Conference (TWK 2004), 2004
#camera calibration, #machine learning
BibTex
Learning Depth
Proceedings of the 7th Tübingen Perception Conference (TWK 2004), 2004
#camera calibration, #machine learning
BibTex
