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 effectiveness of …

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 than humans, …

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 a …

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 can be …

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.