28 citations · 29 across the 2 of their papers we have counts for
2 papers
cs.LG2026★ 28 cited
CEENs: Causality-enforced evolutional networks for solving time-dependent partial differential equations
Jeahan Jung, Heechang Kim, Hyomin Shin +1
Despite the growing popularity of physics-informed neural networks (PINNs), their applicability in the long-time integration of partial differential equations (PDEs) remains constr…
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…