Leírás
In order to interpret environmental stimuli properly and design appropriate actions efficiently the nervous system needs to learn the structure of the environment. In the case of mammals both behavioral studies and electrophysiological measurements indicate that the brain builds an internal model of the environment, which can be used to make inferences based on the sensory experience. This challenge is equivalent to that faced by machine learning when designing artificial agents which can make inferences to perform tasks efficiently. The tools of machine learning, such as generative models and Bayesian inference, provide us an opportunity to quantitatively investigate the internal models and thus to discover the mathematical principles underlying the computations performed by the brain.
The talk is held in English!
Az előadás nyelve angol!