1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models
Kyungryeol Lee, Kyeonghyun Lee, Seongmin Hong +2
Machine unlearning aims to remove specific outputs from trained models, often at the concept level, such as forgetting all occurrences of a particular celebrity or filtering conten…
Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution
Junseo Bang, Joonhee Lee, Kyeonghyun Lee +3
Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-scale super-resolution. Recent approac…
Gradient-free Decoder Inversion in Latent Diffusion Models
Seongmin Hong, Suh Yoon Jeon, Kyeonghyun Lee +2
In latent diffusion models (LDMs), denoising diffusion process efficiently takes place on latent space whose dimension is lower than that of pixel space. Decoder is typically used…
On Exact Inversion of DPM-Solvers
Seongmin Hong, Kyeonghyun Lee, Suh Yoon Jeon +2
Diffusion probabilistic models (DPMs) are a key component in modern generative models. DPM-solvers have achieved reduced latency and enhanced quality significantly, but have posed…