137 citations · 483 across the 17 of their papers we have counts for
9 papers · 1 filter
Noninvasive precision modulation of high-level neural population activity via natural vision perturbations
Guy Gaziv, Sarah Goulding, Ani Ayvazian-Hancock +2
Precise control of neural activity -- modulating target neurons deep in the brain while leaving nearby neurons unaffected -- is an outstanding challenge in neuroscience, generally…
Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations
Yudi Xie, Weichen Huang, Esther Alter +3
Studies of the functional role of the primate ventral visual stream have traditionally focused on object categorization, often ignoring -- despite much prior evidence -- its role i…
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…
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds
Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy +4
Recently, growth in our understanding of the computations performed in both biological and artificial neural networks has largely been driven by either low-level mechanistic studie…
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates
Kohitij Kar, James J DiCarlo
Visual object recognition -- the behavioral ability to rapidly and accurately categorize many visually encountered objects -- is core to primate cognition. This behavioral capabili…
Adversarially trained neural representations may already be as robust as corresponding biological neural representations
Chong Guo, Michael J. Lee, Guillaume Leclerc +4
Visual systems of primates are the gold standard of robust perception. There is thus a general belief that mimicking the neural representations that underlie those systems will yie…