A note on restricted Boltzmann machines and variational autoencoders Online publication date: Thu, 14-Mar-2019
by Jian Zhang
International Journal of Collaborative Intelligence (IJCI), Vol. 2, No. 1, 2019
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.
Online publication date: Thu, 14-Mar-2019
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Collaborative Intelligence (IJCI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org