אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

The brain has recognition capabilities that remain unmatched by computer algorithms. We hypothesize that using matched feedforward-feedback connections, recognition centers of the brain reconstruct an internal copy of inputs using knowledge the brain has previously accumulated, in accordance with a class models called "generative models". Subsequently, it minimizes the error between the internal copy and the input from the environment. We study how this strategy may enable simple flexible learning, scalability, overcome combinatorial problems associated with pattern mixtures, and display cognitive phenomena.