Dne 28. dubna 2023 proběhne od 11:00 v přednáškovém sále 132 (změna místnosti) v kampusu Dejvice (Technická 2) přednáška "Generative Diffusion Models: Key Ideas, Current Practice and Research Challenges". Přednášející: prof. Pietro Michiardi, Ph.D., EURECOM, Sophia Antipolis, France, http://www.eurecom.fr/~michiard
Přednáška bude ve výše uvedeném čase rovněž k dispozici on-line.
Abstract:
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.
Přednáška bude ve výše uvedeném čase rovněž k dispozici on-line.
Abstract:
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.