Deep Generative Models
Deep generative models (DGM) can simulate novel and plausible data (e.g. images or text) making them one of the most intriguing directions in machine learning. My research on Gradient Boosted Flows (GBF) increases the flexibility of the latent space learned by normalizing flow-based DGMs. GBF allows practioners to trade additional time training for better performance.