… supervised learning applications … deep neural networks are popular for supervised learning
applications viz., classification, regression, etc. Besides the type of deep learning architecture…

… Deep learning has led to a paradigm shift in artificial … Machine learning, in general, and
deep learning, in particular, … Here we present the deep learning architecture SchNet that is …

… Deep learning is broadening its scope and gaining more popularity in natural … learning
trend. The purpose of this study is to provide a brief review of deep learning architectures and …

… us to investigate methods of predicting air quality based on deep architecture models. In
this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method …

… learning and mathematical statistics of deep learning, or the mathematics relevant to the
computational complexity of deep learning, … be represented by deep learning neural networks. …

… Deep learning Deep learning architectures Architectures have revolutionized the analytical
… chapter, we will discuss multiple deep learning Deep learning architectures Architectures …

… learning features and a corresponding similarity metric for person re-identification. We present
a deep convolutional architecture … Novel elements of our architecture include a layer that …

… This paper showed state-of-the-art machine translation results with the architecture introduced
in ref. 72, with a recurrent network trained to read a sentence in one language, produce a …

… Here we describe a new deep learning architecture, Deep Stacking Network (DSN),
which attacks the learning scalability problem. This section is based in part on the recent …

… of deep learning on the detection of abuse in all its forms with a unified architecture. … -specific,
features, we design a neural network architecture that is able to digest all available input (…