In this talk, we will discuss a special class of generative models, called diffusion processes, and present their applications as well as challenges that the scientific community is currently addressing.
We will first provide some background for the generative modelling task, and introduce the basic tools that are required to understand diffusion processes. We will then quickly overview the general topic of energy-based modelling, give some example applications, and focus on score-based generative models. Our goal is to provide an overview of the theory behind score-based models, but also to demystify them and suggest a practical interpretation of these methods.
We will conclude the talk with some challenges we are currently addressing, including going beyond image data, multi-modality, and methodological advances that are required to improve the practical application of such exciting new methods.
