Here-Liu's Stars
nlesc-dirac/pytorch
Improved LBFGS and LBFGS-B optimizers in PyTorch.
AmeyaJagtap/XPINNs
Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations
AmeyaJagtap/Conservative_PINNs
We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation property of cPINN is obtained by enforcing the flux continuity in the strong form along the sub-domain interfaces.
sayin/Physics_informed_GANs_turbulent_flows
Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution (DNS) fields without solving NS equations numerically.
Shengfeng233/PINN-MPI
parallel PINNs; RANS equations; spatiotemporal parallel; PINNs
Shengfeng233/PINN-for-NS-equation
A pytorch implementaion of physics informed neural networks for two dimensional NS equation
Shengfeng233/PINN-for-turbulence
A pytorch implementation of several approaches using PINN to slove turbulent flow
gear106/Tubulence-Super-Resolution
Super-resolution reconstruction of turbulent flow