Chengxu Zhuang

Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation

This paper develops a computational model of mouse visual cortex, finding that self-supervised contrastive learning produces better matches to mouse cortex than supervised methods, suggesting a resource-efficient, general-purpose visual system.

Unsupervised Neural Network Models of the Ventral Visual Stream

This paper shows that unsupervised neural networks can model primate ventral visual stream responses as well as supervised methods, with brain-like representations from limited data.