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
arXiv, 2018
#v1, #system identification, #microns, #convolutional neural network, #rotation equivariance
URL, PDF, BibTex

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
bioRxiv, 2017
URL, DOI, 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

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

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