cics-nd / pde-surrogateLinks
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
☆150Updated 5 years ago
Alternatives and similar repositories for pde-surrogate
Users that are interested in pde-surrogate are comparing it to the libraries listed below
Sorting:
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated 2 years ago
- ☆150Updated 3 years ago
- ☆63Updated 6 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆140Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 years ago
- ☆98Updated 3 years ago
- ☆222Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- ☆112Updated 7 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆82Updated 3 weeks ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆41Updated 2 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆107Updated 5 years ago
- hPINN: Physics-informed neural networks with hard constraints☆142Updated 3 years ago
- Applications of PINOs☆133Updated 2 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 5 years ago
- ☆64Updated 2 years ago
- ☆175Updated last year
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆150Updated 5 years ago
- ☆36Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆154Updated last year
- ☆54Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆75Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆209Updated 2 years ago
- ☆189Updated 5 months ago