cselab / odil
ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equations.
☆101Updated 2 months ago
Alternatives and similar repositories for odil:
Users that are interested in odil are comparing it to the libraries listed below
- physics-informed neural network for elastodynamics problem☆132Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆76Updated 2 years ago
- ☆91Updated 3 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆43Updated 10 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆84Updated last year
- Original implementation of fast PINN optimization with RBA weights