Topic: accelerated inference

Neural circuits must perform probabilistic computations to efficiently process noisy sensory information. Sampling codes propose that single neuron variability is a signature of probabilistic computation, and corresponds to sampling the space of possible solutions in proportion to their posterior probability. Under this hypothesis, the neural code defines how variables inferred by the network are represented in single neurons. Compared to other proposed probabilistic codes, the capacity of sampling codes scales with the number of neurons, but their convergence speed scales poorly with dimensio