Core Ideas behind Flow based Generative AI Models

Flow-based generative models are a powerful class of deep generative models, and in this video, we dive into Continuous Normalizing Flows (CNF)-an extension that leverages Neural ODEs to model complex distributions with continuous transformations. We start by exploring vector fields and ordinary differential equations (ODEs), then implement simple yet effective CNFs that transform samples from a simple distribution like a standard normal into target distributions. Along the way, we discuss techniques like the Euler method, the adjoint method, and trace estimation—key concepts that make cont…