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Abstract:
The new king of image generation is here; in the last couple of years, diffusion models have displaced GAN’s as de facto approach to produce realistic high resolution images. With the introduction of large models like Stable Diffusion, GLIDE, DALL-E2, and Imagen, denoising diffusion probabilistic models (DDPM) have shown remarkable superiority in conditional image generation. In this talk, we will explore the history of these developments, and provide some intuition about the mechanisms used to train them.
Laboratory for Simulation and Modelling
SDSC Hub @ PSI