Toward Statistically Optimal Diffusion Generative Models: Accuracy, Complexity, and Privacy

This research project explores the statistical aspects of diffusion models, an emerging class of generative modeling techniques that are transforming current practices in image and video synthesis, scientific simulation, inverse problems, and offline reinforcement learning. The project will apply information theory methods to explain when and why…