The Neural Coding Framework for Learning Generative Models
How can a probabilistic generative model of data be learned in a neurobiologically-plausible fashion without the popular algorithm known as backpropagation of errors? This paper seeks to answer this question by developing a computational framework referred to as neural generative coding.
