3 papers
physics.comp-ph2025
Hybrid Boundary Physics-Informed Neural Networks for Solving Navier-Stokes Equations with Complex Boundary
Chuyu Zhou, ianyu Li, Chenxi Lan +7
Physics-informed neural networks (PINN) have achieved notable success in solving partial differential equations (PDE), yet solving the Navier-Stokes equations (NSE) with complex bo…
physics.flu-dyn2024
Physics-Informed Neural Networks with Complementary Soft and Hard Constraints for Solving Complex Boundary Navier-Stokes Equations
Chuyu Zhou, Tianyu Li, Chenxi Lan +7
Soft- and hard-constrained Physics Informed Neural Networks (PINNs) have achieved great success in solving partial differential equations (PDEs). However, these methods still face…
q-fin.CP2024
Fourier Neural Network Approximation of Transition Densities in Finance
Rong Du, Duy-Minh Dang
This paper introduces FourNet, a novel single-layer feed-forward neural network (FFNN) method designed to approximate transition densities for which closed-form expressions of thei…