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The brain has recognition capabilities that remain unmatched by computer algorithms. We hypothesize that 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 a simple, flexible learning strategy, overcome known combinatorial problems associated with pattern mixtures, and display cognitive phenomena. Host: Garrett Kenyon, gkenyon@lanl.gov, 7-1900 |