What does "Normalizing Flow Model" mean?
Table of Contents
A normalizing flow model is a type of machine learning technique used to understand and generate data. It transforms complex data into simpler forms that are easier to work with. This process involves changing the data in such a way that it remains true to its original characteristics.
How It Works
Normalizing flow models take raw data, such as images, and break it down into smaller, more manageable parts. By doing this, they can learn the patterns and features of the data. This learned information can then be used to create new images or analyze existing ones.
Applications
These models are useful for various tasks including image generation and understanding. They help in creating high-quality images and can identify different elements within the images. Using normalizing flow models can lead to better performance in tasks that involve both images and text.