28 citations · 28 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…
cs.LG2026
Physics-Informed Laplace Neural Operator for Solving Partial Differential Equations
Heechang Kim, Qianying Cao, Hyomin Shin +3
Neural operators have emerged as fast surrogate solvers for parametric partial differential equations (PDEs). However, purely data-driven models often require extensive training da…