Nature Communications (Jul 2017)
Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback
Abstract
Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.