Approximating Bayesian inference with a sparse distributed memory system

  title={Approximating Bayesian inference with a sparse distributed memory system},
  author={Joshua T. Abbott and Jessica B. Hamrick and Thomas L. Griffiths},
Probabilistic models of cognition have enjoyed recent success in explaining how people make inductive inferences. Yet, the difficult computations over structured representations that are often required by these models seem incompatible with the continuous and distributed nature of human minds. To reconcile this issue, and to understand the implications of constraints on probabilistic models, we take the approach of formalizing the mechanisms by which cognitive and neural processes could… CONTINUE READING


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