A note on restricted Boltzmann machines and variational autoencoders. Issue 1 (2019)

• Record Type: Journal Article
• Authors: Zhang, Jian
• Is Part Of: International journal of collaborative intelligence. Volume 2:Issue 1(2019)
• Page Start: 66
• Page End: 74
• Publication Date: 2019
• Subjects: restricted Boltzmann machines -- RBMs -- variational autoencoders -- VAEs -- generative adversarial nets -- deep neural nets; Computational intelligence -- Periodicals; Cognitive science -- Periodicals; Information science -- Periodicals; 006.305
• Languages: English
• ISSNs: 2051-7122

Abstract

This paper mainly introduces the theory and the abilities of generating images of restricted Boltzmann machines (RBMs) and variational autoencoders (VAEs). First, we introduce these models, which can be treated as the basic blocks of deep neural nets. Second, this paper introduces the ability of generating images based on these models. Lastly, this paper introduces the hybrid model based on RBMs and VAEs and another model called a Boltzmann encoded adversarial machine (BEAM). The experiments show the effectiveness of the hybrid models.