2026
There and Back Again: On the relation between Noise and Image Inversions in Diffusion Models
ICLR 2026poster
Diffusion Models achieve state-of-the-art performance in generating new samples but lack a low-dimensional latent space that encodes the data into editable features. Inversion-based methods address this by reversing the denoising trajectory, transferring images to their approximated starting noise.…