4 citations · 4 across the 2 of their papers we have counts for
2 papers
stat.ML2023
A Bayesian sparse factor model with adaptive posterior concentration
Ilsang Ohn, Lizhen Lin, Yongdai Kim
In this paper, we propose a new Bayesian inference method for a high-dimensional sparse factor model that allows both the factor dimensionality and the sparse structure of the load…
stat.ML2023★ 4 cited
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong, Dongyoon Yang, Jongjin Lee +3
Bayesian approaches for learning deep neural networks (BNN) have been received much attention and successfully applied to various applications. Particularly, BNNs have the merit of…