Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive lecture on machine learning techniques for generating new molecules, covering fundamental concepts from basic autoencoders to advanced applications in drug discovery. Delve into the theoretical foundations of variational autoencoders (VAEs), examining their probabilistic perspective, information theory concepts, and the mathematics behind Bayes' Law and evidence lower bounds. Master the intricacies of VAE architecture, including the challenges in variational computing and the structure of latent spaces, before advancing to Generative Adversarial Networks (GANs). Learn how junction tree VAEs are specifically applied to small molecule generation, culminating in practical applications of AI for identifying candidate antibiotics. Access complementary materials including detailed notes, slides, and a dedicated chapter to enhance understanding of these cutting-edge molecular generation techniques.