8 citations · 9 across the 2 of their papers we have counts for
2 papers
stat.ML2022★ 1 cited
Bayesian deep learning framework for uncertainty quantification in high dimensions
Jeahan Jung, Minseok Choi
We develop a novel deep learning method for uncertainty quantification in stochastic partial differential equations based on Bayesian neural network (BNN) and Hamiltonian Monte Car…
nlin.AO2016★ 8 cited
Dimension reduction in heterogeneous neural networks: generalized Polynomial Chaos (gPC) and ANalysis-Of-VAriance (ANOVA)
Minseok Choi, Tom Bertalan, Carlo R. Laing +1
We propose, and illustrate via a neural network example, two different approaches to coarse-graining large heterogeneous networks. Both approaches are inspired from, and use tools…