[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …
domains. This new field of machine learning has been growing rapidly and has been …
The history began from alexnet: A comprehensive survey on deep learning approaches
Max-margin deep generative models for (semi-) supervised learning
Deep generative models (DGMs) can effectively capture the underlying distributions of
complex data by learning multilayered representations and performing inference. However …
complex data by learning multilayered representations and performing inference. However …
ZhuSuan: A library for Bayesian deep learning
In this paper we introduce ZhuSuan, a python probabilistic programming library for Bayesian
deep learning, which conjoins the complimentary advantages of Bayesian methods and …
deep learning, which conjoins the complimentary advantages of Bayesian methods and …
Learning to generate with memory
Memory units have been widely used to enrich the capabilities of deep networks on
capturing long-term dependencies in reasoning and prediction tasks, but little investigation …
capturing long-term dependencies in reasoning and prediction tasks, but little investigation …