MIT 6.S191: Introduction to Deep Learning - MIT 6.S191 (2021): Deep Generative Modeling

MIT 6.S191 (2021): Introduction to Deep Learning Deep Generative Modeling Lecturer: Ava Soleimany January 2021 For all lectures, slides, and lab materials: http://introtodeeplearning.com​ Lecture Outline 0:00​ - Introduction 6:03 - Why care about generative models? 8:56​ - Latent variable models 11:31​ - Autoencoders 17:00​ - Variational autoencoders 24:30 - Priors on the latent distribution 34:38​ - Reparameterization trick 38:14​ - Latent perturbation and disentanglement 41:25 - Debiasing with VAEs 43:42​ - Generative adversarial networks 46:14​ - Intuitions behind GANs 48:27 - Training GANs 52:57 - GANs: Recent advances 57:15 - CycleGAN of unpaired translation 1:01:01​ - Summary Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!