CS480/680 Lecture 23: Normalizing flows (Priyank Jaini) Published 2019-07-27 Download video MP4 360p Recommendations 1:14:55 CS480/680 Lecture 24: Gradient boosting, bagging, decision forests 56:29 2021 3.1 Variational inference, VAE's and normalizing flows - Rianne van den Berg 55:51 CS480/680 Lecture 21: Generative networks (variational autoencoders and GANs) 56:16 Flow Matching for Generative Modeling (Paper Explained) 00:39 Elon Musk Laughs at the Idea of Getting a PhD... and Explains How to Actually Be Useful! 1:01:31 CS480/680 Lecture 17: Hidden Markov Models 58:03 Max Welling - Make VAEs Great Again: Unifying VAEs and Flows 12:31 What are Normalizing Flows? 21:44 The weirdest paradox in statistics (and machine learning) 45:18 Shape Analysis (Lectures 17, extra content): Continuous normalizing flows 1:53:05 Variational Inference: Foundations and Modern Methods (NIPS 2016 tutorial) 58:54 Introduction to Normalizing Flows (ECCV2020 Tutorial) 1:40:41 CS480/680 Lecture 18: Recurrent and recursive neural networks 1:07:24 CS480/680 Lecture 22: Ensemble learning (bagging and boosting) 1:07:12 Gail Weiss: Thinking Like Transformers 1:13:25 CS480/680 Lecture 5: Statistical Linear Regression 29:29 Denoising Diffusion Probabilistic Models | DDPM Explained Similar videos 08:49 CS480/680 Lecture 6: Normalizing flows (Priyank Jaini) 13:53 Generative Modeling - Normalizing Flows 38:58 CS480/680 Lecture 20: Autoencoders 15:58 Stochastic Normalizing Flows 09:12 1. Normalizing flows - theory and implementation - 1D flows 20:34 Graph Normalizing Flows 10:29 Tutorial 11: Normalizing Flows (Part 1) 1:22:38 CS480/680 Lecture 19: Attention and Transformer Networks 59:24 Normalizing Flows - Motivations, The Big Idea, & Essential Foundations 01:22 Priyank Jaini Resume More results