Sparse autoencoders are derived as MAP estimators for a continuous topic model, yielding a reusable topic modeling framework that produces coherent topics on text and image datasets.
Sparse feature learning for deep belief networks
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Sparse Autoencoders are Topic Models
Sparse autoencoders are derived as MAP estimators for a continuous topic model, yielding a reusable topic modeling framework that produces coherent topics on text and image datasets.