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

Tianhua Chen's 195-page primer provides a mathematically rigorous yet accessible introduction to generative AI foundations, tracing connections across major model families including PCA, VAEs, diffusion models, normalizing flows, GANs, and energy-based models. The book emphasizes derivations and theoretical understanding rather than surveying recent architectures, targeting mathematically curious researchers, practitioners, and students seeking to build foundational knowledge in generative modeling.