35 citations · 90 across the 11 of their papers we have counts for
3 papers · 1 filter
Understanding Inhibition Through Maximally Tense Images
Chris Hamblin, Srijani Saha, Talia Konkle +1
We address the functional role of 'feature inhibition' in vision models; that is, what are the mechanisms by which a neural network ensures images do not express a given feature? W…
Feature Accentuation: Revealing 'What' Features Respond to in Natural Images
Chris Hamblin, Thomas Fel, Srijani Saha +2
Efforts to decode neural network vision models necessitate a comprehensive grasp of both the spatial and semantic facets governing feature responses within images. Most research ha…
How does the primate brain combine generative and discriminative computations in vision?
Benjamin Peters, James J. DiCarlo, Todd Gureckis +10
Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as we…