Flow Matching

KL-Divergence flow-matching Generative models are very good / best in class approximators of a complex probabilistic equation/distribution that we most of the times have no idea of !! Images modality : All images in the world are from a very complex distribution of pixels that gives direction , based on the prompts , and are dependent of what the user wants , and as it very complex to model that distribution we rely on NN to predict it , hence we have diffusion models ...

The pre-requisites for this blog post is Journey till diffusion model Generative image models We start with some image dataset, lets say x ~ X (where x is a sample and X is the dataset) this x belongs to R_(1024 x 1024 x 3) space and doing any operations in this space is very hard so we try to do these in a lower dimension (z) z belongs to R_(1 x 512) ...