Deep learning has already achieved remarkable results in many fields. Now it's making
waves throughout the sciences broadly and the life sciences in particular. This practical …

Although deep learning has historical roots going back decades, neither the term" deep
learning" nor the approach was popular just over five years ago, when the field was …

Deep learning has been widely recognized as the representative advances of machine
learning or artificial intelligence in general nowadays [1, 2]. This can be attributed to the …

Artificial intelligence (AI) is advancing very rapidly. I've had a front-row seat for a lot of the
recent progress—first at Bell Labs (which was renamed AT&T Labs in 1996, while I was …

Deep learning is a subfield of machine learning that considers computational models with
multiple processing layers [1, 3, 6]. At the core of all deep learning approaches lies …

Deep neural networks ('deep learning') have emerged as a technology of choice to tackle
problems in speech recognition, computer vision, finance, etc. However, adoption of deep …

The ability of multilayer back-propagation networks to learn complex, high-dimensional,
nonlinear mappings from large collections of examples makes them obvious candidates for …

While artificial neural networks have been in existence for over half a century, it was not until
year 2010 that they had made a significant impact on speech recognition with a deep form of …

As a major breakthrough in artificial intelligence, deep learning has achieved very
impressive success in solving grand challenges in many fields including speech recognition …

Currently, deep neural networks are the state of the art on problems such as speech
recognition and computer vision. In this paper we empirically demonstrate that shallow feed …