1 citations · 1 across the 4 of their papers we have counts for
4 papers
Upsample Guidance: Scale Up Diffusion Models without Training
Juno Hwang, Yong-Hyun Park, Junghyo Jo
Diffusion models have demonstrated superior performance across various generative tasks including images, videos, and audio. However, they encounter difficulties in directly genera…
Resolution Chromatography of Diffusion Models
Juno Hwang, Yong-Hyun Park, Junghyo Jo
Diffusion models generate high-resolution images through iterative stochastic processes. In particular, the denoising method is one of the most popular approaches that predicts the…
Mirror descent of Hopfield model
Hyungjoon Soh, Dongyeob Kim, Juno Hwang +1
Mirror descent is an elegant optimization technique that leverages a dual space of parametric models to perform gradient descent. While originally developed for convex optimization…
Tractable loss function and color image generation of multinary restricted Boltzmann machine
Juno Hwang, Wonseok Hwang, Junghyo Jo
The restricted Boltzmann machine (RBM) is a representative generative model based on the concept of statistical mechanics. In spite of the strong merit of interpretability, unavail…