Deep Generative Models: Part 2Explores deep generative models, including mixtures of multinomials, PCA, deep autoencoders, convolutional autoencoders, and GANs.
Score-based Generative ModellingExplores score-based generative modelling through stochastic differential equations, emphasizing denoising score matching and diffusion probabilistic models.
Supervised Learning EssentialsIntroduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.
