67 citations · 93 across the 19 of their papers we have counts for
4 papers · 1 filter
Variational bagging: a robust approach for Bayesian uncertainty quantification
Shitao Fan, Ilsang Ohn, David Dunson +1
Variational Bayes methods are popular due to their computational efficiency and adaptability to diverse applications. In specifying the variational family, mean-field classes are c…
Online conformal inference with retrospective adjustment for faster adaptation to distribution shift
Jungbin Jun, Ilsang Ohn
Conformal prediction has emerged as a powerful framework for constructing distribution-free prediction sets with guaranteed coverage assuming only the exchangeability assumption. H…
Knowledge Distillation of Uncertainty using Deep Latent Factor Model
Sehyun Park, Jongjin Lee, Yunseop Shin +2
Deep ensembles deliver state-of-the-art, reliable uncertainty quantification, but their heavy computational and memory requirements hinder their practical deployments to real appli…
Nonparametric estimation of a factorizable density using diffusion models
Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn +1
In recent years, diffusion models, and more generally score-based deep generative models, have achieved remarkable success in various applications, including image and audio genera…