Simona Temereanca

Convolutional dictionary learning based auto-encoders for natural exponential-family distributions

We introduce a class of auto-encoder neural networks tailored to data from the natural exponential family (e.g., count data). The architectures are inspired by the problem of learning the filters in a convolutional generative model with sparsity constraints, often referred to as convolutional dictio…