Publications by S. Cadena
Preprints
K.-K. Lurz,
M. Bashiri,
K. F. Willeke,
A. K. Jagadish,
E. Wang,
E. Y. Walker,
S. Cadena,
T. Muhammad,
et al.
Generalization in data-driven models of primary visual cortex
bioRxiv, 2020
URL, Code, BibTex
Generalization in data-driven models of primary visual cortex
bioRxiv, 2020
URL, Code, BibTex
Journal Articles
S. A. Cadena,
G. H. Denfield,
E. Y. Walker,
L. A. Gatys,
A. S. Tolias,
M. Bethge, and
A. S. Ecker
Deep convolutional models improve predictions of macaque V1 responses to natural images
PLoS Computational Biology, 2019
URL, DOI, PDF, BibTex
Deep convolutional models improve predictions of macaque V1 responses to natural images
PLoS Computational Biology, 2019
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
S. A. Cadena,
M. A. Weis,
L. A. Gatys,
M. Bethge, and
A. S. Ecker
Diverse feature visualizations reveal invariances in early layers of deep neural networks
The European Conference on Computer Vision (ECCV), 2018
URL, BibTex
Diverse feature visualizations reveal invariances in early layers of deep neural networks
The European Conference on Computer Vision (ECCV), 2018
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
S. Cadena,
A. Ecker,
G. Denfield,
E. Walker,
A. Tolias, and
M. Bethge
A goal-driven deep learning approach for V1 system identification
Computational and Systems Neuroscience Meeting (COSYNE 2017), 2017
BibTex
A goal-driven deep learning approach for V1 system identification
Computational and Systems Neuroscience Meeting (COSYNE 2017), 2017
BibTex
S. Cadena,
A. Ecker,
G. Denfield,
E. Walker,
A. Tolias, and
M. Bethge
A goal-driven deep learning approach for V1 system identification
Bernstein Conference 2016, 2016
DOI, BibTex
A goal-driven deep learning approach for V1 system identification
Bernstein Conference 2016, 2016
DOI, BibTex
