I am interested in developing computational models of neural processing to understand how neural systems represent, manipulate and learn about uncertainty, particularly in information processing tasks that change on fast time-scales. My research has focused on probabilistic approaches to dynamic population coding and learning in stochastic neural networks. I am also interested in developing, constraining and testing Bayesian theories of sensory perception using hard psychophysical data.
Rama Natarajan
Ph.D. Candidate
Supervised by Prof. Richard Zemel,
Machine Learning Group,
Department of Computer Science,
University of Toronto.
email: rama[at]cs[dot]toronto[dot]edu
