Which process involves a model learning to remove noise from images?SamplingReverse diffusionForward diffusionGANs

The process that involves a model learning to remove noise from images is Reverse diffusion.

Explanation:

• Reverse diffusion refers to the process used in denoising models, particularly in diffusion models where noise is gradually added to an image and then a reverse process is applied to recover the image by removing that noise. This technique allows the model to learn how to reconstruct clear images from noisy versions.

In contrast:

• Sampling typically refers to selecting a subset of data from a larger dataset.
• Forward diffusion is the process of adding noise to the image, not removing it.
• GANs (Generative Adversarial Networks) are a type of model used for generating new data samples but do not specifically focus on noise removal.

Thus, the correct answer is Reverse diffusion.