Denoising Diffusion Models are a type of generative modelling which serves backbone of recent advances in image synthesis including Dall-E 2, Midjourney, and Imagen. These models utilise an iterative denoising process during inference to produce high quality samples. In this talk we explore the fundamentals of diffusion models, the intuition behind them, how they work in practice, and how they may be generalised to a wide range of applications.
Kevin Eloff MEng graduate from Stellenbosch Univeristy, with a thesis focused on combining speech processing and multi-agent reinforcement learning. Currently working at InstaDeep as a BioAI research engineer.
16 August 2023