MathyAIwithMike

MathyAIwithMike discusses a new paper reviving Normalizing Flows (NFs) by combining them with techniques from diffusion models, like classifier guidance, and Tweedie's formula. NFs learn a reversible mapping between a simple distribution and the data, allowing likelihood calculation. This paper improves robustness by training on noisy data and using Tweedie's formula to estimate clean outputs. Classifier guidance, borrowed from diffusion models, steers the sampling process to generate specific classes. Find the paper on arXiv (link in show notes!).