The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer

Generative Models: Principles, Architectures, and Applications

arXiv:2608. 08101v1 Announce Type: new Abstract: Generative AI has emerged as one of the most transformative forces in modern artificial intelligence, reshaping how we create, imagine, and interact with digital content.

Notes on generative modeling: flow matching, diffusion, optimal transport and Schr{ö}dinger bridge

These notes recapitulate the high level mathematical principles behind different techniques for generative modeling. I show the connections between optimal transport and standard techniques such as Schr{ö}dinger bridge and flow matching.

On the quantitative analysis of decoder-based generative models

Generative models

This post describes four projects that share a common theme of enhancing or using generative models, a branch of unsupervised learning techniques in machine learning. In addition to describing our work, this post will tell you a bit more about generative models: what they are, why they are important, and where they might be going.

Notes on generative modeling: flow matching, diffusion, optimal transport and Schr{\"o}dinger bridge

arXiv:2606. 30053v1 Announce Type: cross Abstract: These notes recapitulate the high level mathematical principles behind different techniques for generative modeling.

A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models