34 citations · 102 across the 8 of their papers we have counts for
4 papers · 1 filter
Fast Ensembling with Diffusion Schrödinger Bridge
Hyunsu Kim, Jongmin Yoon, Juho Lee
Deep Ensemble (DE) approach is a straightforward technique used to enhance the performance of deep neural networks by training them from different initial points, converging toward…
Sequential Flow Straightening for Generative Modeling
Jongmin Yoon, Juho Lee
Straightening the probability flow of the continuous-time generative models, such as diffusion models or flow-based models, is the key to fast sampling through the numerical solver…
Diversity Matters When Learning From Ensembles
Giung Nam, Jongmin Yoon, Yoonho Lee +1
Deep ensembles excel in large-scale image classification tasks both in terms of prediction accuracy and calibration. Despite being simple to train, the computation and memory cost…
Adversarial purification with Score-based generative models
Jongmin Yoon, Sung Ju Hwang, Juho Lee
While adversarial training is considered as a standard defense method against adversarial attacks for image classifiers, adversarial purification, which purifies attacked images in…