Compressive neural representation of sparse, high-dimensional probabilities

NeurIPS 2012 Zachary Pitkow

This paper shows how sparse, high-dimensional probability distributions could be represented by neurons with exponential compression. The representation is a novel application of compressive sensing to sparse probability distributions rather than to the usual sparse signals... (read more)

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