limjoowon / maxwellnetLinks
☆63Updated 2 years ago
Alternatives and similar repositories for maxwellnet
Users that are interested in maxwellnet are comparing it to the libraries listed below
Sorting:
- Neural operator surrogates for electromagnetic inverse design☆44Updated last year
- hPINN: Physics-informed neural networks with hard constraints☆149Updated 4 years ago
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆119Updated 2 weeks ago
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.☆36Updated last year
- ☆103Updated 4 years ago
- Use Fourier transform to learn operators in differential equations.☆40Updated 4 years ago
- Physics Constrained Neural Networks☆12Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- Deep-learning iterative solver for the heterogeneous 2D Helmholtz equation☆32Updated 2 years ago
- ☆14Updated 4 years ago
- Physics Informed Neural Networks☆20Updated 5 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- ☆37Updated 2 years ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆336Updated 2 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆158Updated 10 months ago
- Jaxwell is JAX + Maxwell☆24Updated last year
- ☆155Updated 3 years ago
- ☆33Updated 3 years ago
- ☆14Updated last year
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆75Updated 6 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆100Updated 3 years ago
- This Matlab code is used to solve inverse scattering problem with convolutional neural network by BPS.☆56Updated 3 years ago
- A collection of inverse design challenges☆55Updated last month
- ☆52Updated 11 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 2 years ago
- Code for "Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions"☆16Updated 3 years ago
- ☆170Updated last year
- MIONet: Learning multiple-input operators via tensor product☆39Updated 3 years ago