161 citations · 217 across the 5 of their papers we have counts for
5 papers
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…
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence
Yi Ma, Doris Tsao, Heung-Yeung Shum
Ten years into the revival of deep networks and artificial intelligence, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture…
A topological solution to object segmentation and tracking
Thomas Tsao, Doris Y. Tsao
The world is composed of objects, the ground, and the sky. Visual perception of objects requires solving two fundamental challenges: segmenting visual input into discrete units, an…
Neural Networks with Recurrent Generative Feedback
Yujia Huang, James Gornet, Sihui Dai +4
Neural networks are vulnerable to input perturbations such as additive noise and adversarial attacks. In contrast, human perception is much more robust to such perturbations. The B…
Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons
Irina Higgins, Le Chang, Victoria Langston +4
Deep supervised neural networks trained to classify objects have emerged as popular models of computation in the primate ventral stream. These models represent information with a h…