In Section 5, as a major example in the hybrid deep network cate-gory, we present in detail the deep neural networks with unsupervised and largely generative pre-training to boost the …

Ng put the “deep” in deep learning, which describes all the layers in these neural networks. Today, image recognition by machines trained via deep learning in some scenarios is better …

Here, four deep generative networks such as DBN, Deep Boltzmann Machine (DBM), Generative Adversarial Network (GAN), and Variational Autoencoder (VAE) are discussed.

• Deep learning has revolutionized pattern recognition, introducing technology that now powersawiderangeoftechnologies,includingcomputervision,naturallanguageprocess- …

This monograph discusses the emerging theory of deep learning. It originated from notes by the lecturers at a graduate seminar taught at Princeton University in Fall 2019 in conjunction with …

s new notation. When run with a large number of linear units, linear algebra in general, and deep learning training in particular can be very time consuming. However, a great many problems …

What is Deep Learning? Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction.