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The Evolution of Neural Generative Models

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If you have a question about this talk, please contact Leandro Minku.

Within the paradigm of unsupervised learning it is becoming increasingly clear that the brain makes generative models of the environment that can explain observations in a parsimonious way. This helps with inference about the current environmental state and predictions of future environmental states given observations. What kinds of generative model are there in principle? What methods exist that allow these generative models to be learned? I propose a set of major transitions in the evolution of cognition in which new classes of generative model have evolved, along with new methods for learning such models. I consider the neural correlates of these transitions.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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