pierremtb / POD-UQNN
Uncertainty Quantification in the POD-NN framework
☆19Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for POD-UQNN
- DAFI: Ensemble based data assimilation and field inversion, repository for internal development☆49Updated last year
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆11Updated 3 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆20Updated last year
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆19Updated 3 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆9Updated last year
- POD-PINN code and manuscript☆45Updated 4 years ago
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆13Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆44Updated 4 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆89Updated 5 years ago
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆16Updated 3 years ago
- CU-BEN serial version: geometric and material nonlinear static and transient dynamic structural analysis/ linear acoustic fluid structure…☆11Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆28Updated 4 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆18Updated last year
- Multi-fidelity reduced-order surrogate modeling☆11Updated last year
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆28Updated 2 years ago
- ☆24Updated 6 years ago
- Machine learning of linear differential equations using Gaussian processes☆22Updated 6 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆39Updated 6 years ago
- Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.☆17Updated 5 years ago
- ☆61Updated 5 years ago
- Numerical tool for Construction of Reduced-order models for fluid flows.☆30Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆27Updated last year
- ☆11Updated 2 years ago
- Python tools for non-intrusive reduced order modeling☆17Updated 3 months ago
- Uncertainty Quantification of RANS Data-Driven Turbulence Modeling☆54Updated 3 years ago
- Physics informed neural network (PINN) for the 1D Heat equation☆11Updated last year
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆54Updated last year
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆15Updated 3 years ago
- Tensor Basis Neural Network for Scalar Mixing☆10Updated last year