Two of the earliest forms of generative machine learning algorithms are Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE). Despite being developed at approximately the same time, their functionality and structure are markedly different. This project aims to compare these two networks when trained on two different datasets and analyze the differences in their output and runtime in reference to their structure.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Wilusz, Jacob

Subject

• Innovation
• Project-Based Learning
• Computing
• Learning

Publisher

• Worcester Polytechnic Institute

Identifier

• 123883
• E-project-080824-204855

Advisor

• Heineman, George T.
• Sun, Yu-Shan

Year

• 2024

UN Sustainable Development Goals

• Not Specified

Date created

• 2024-08-08

Resource type

• Major Qualifying Project

Major

• Computer Science

Source

• E-project-080824-204855

Rights statement

• In Copyright

最新修改

• 2024-09-19