Generative artificial intelligence (AI) might be best known from text or image-creating applications like ChatGPT or Stable Diffusion. But its usefulness beyond that is being shown in more and more different scientific fields. In their recent work, to be presented at the upcoming International Conference on Learning Representations (ICLR), researchers from the Center for Advanced Systems Understanding (CASUS) at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) in collaboration with colleagues from Imperial College London and University College London have provided a new open-source algorithm called Conditional Variational Diffusion Model. Based on generative AI, this model improves the quality of images by reconstructing them from randomness. In addition, the CVDM is computationally less expensive than established diffusion models -- and it can be easily adapted for a variety of applications.
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