Normalizing flow

A normalizing flow is a machine learning technique that transforms complex, difficult-to-understand probability distributions into simple, well-behaved ones through a series of reversible mathematical operations. Think of it like a sophisticated recipe that gradually untangles a tangled ball of yarn into a neat, straight line, allowing computers to understand and generate data from intricate patterns in images, molecules, or other domains. This approach is powerful because it lets scientists and AI systems work with complicated real-world data while maintaining the ability to reverse the process and create new samples.