Tag
#numerics
2 insights
- engineering · arxiv/cs.LG · 8 min
Learning turbulence closures via nudging sidesteps solver backprop
A data-assimilation-inspired approach trains neural network turbulence models on DNS data without embedding them in solvers, reducing computational cost and improving stability.
Apr 28, 2026 Read → - engineering · arxiv/cs.LG · 4 min
Hybrid PINNs: Finite-Difference Regularization for Physics Solvers
Adding weak finite-difference gradient penalties to physics-informed neural networks improves boundary accuracy without replacing automatic-differentiation residuals.
Apr 17, 2026 Read →