4 citations · 7 across the 2 of their papers we have counts for
5 papers
High-contrast "gaudy" images improve the training of deep neural network models of visual cortex
Benjamin R. Cowley, Jonathan W. Pillow
A key challenge in understanding the sensory transformations of the visual system is to obtain a highly predictive model of responses from visual cortical neurons. Deep neural netw…
Unifying and generalizing models of neural dynamics during decision-making
David M. Zoltowski, Jonathan W. Pillow, Scott W. Linderman
An open question in systems and computational neuroscience is how neural circuits accumulate evidence towards a decision. Fitting models of decision-making theory to neural activit…
Fast shared response model for fMRI data
Hugo Richard, Lucas Martin, Ana Luısa Pinho +2
The shared response model provides a simple but effective framework to analyse fMRI data of subjects exposed to naturalistic stimuli. However when the number of subjects or runs is…
Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations
Stephen L. Keeley, David M. Zoltowski, Yiyi Yu +3
Gaussian Process Factor Analysis (GPFA) has been broadly applied to the problem of identifying smooth, low-dimensional temporal structure underlying large-scale neural recordings.…
Shared Representational Geometry Across Neural Networks
Qihong Lu, Po-Hsuan Chen, Jonathan W. Pillow +3
Different neural networks trained on the same dataset often learn similar input-output mappings with very different weights. Is there some correspondence between these neural netwo…