paraklas / NARGP
Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.
☆63Updated 8 years ago
Alternatives and similar repositories for NARGP:
Users that are interested in NARGP are comparing it to the libraries listed below
- ☆37Updated last year
- Multi-fidelity classification with Gaussian process☆16Updated last year
- ☆62Updated 5 years ago
- Multi-fidelity Gaussian Process☆26Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆68Updated 4 years ago
- ☆37Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- Multi-fidelity reduced-order surrogate modeling☆22Updated this week
- Multi Fidelity Monte Carlo☆25Updated 5 years ago
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆30Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆65Updated last year
- Update PDEKoopman code to Tensorflow 2☆23Updated 4 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆56Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 7 years ago
- Multifidelity Kriging, Efficient Global Optimization☆18Updated 6 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆30Updated 2 years ago
- Tools to construct surrogate models based on Hermitian polynomial bases. Includes full-factorial and sparse polynomial chaos expansions v…☆10Updated 6 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆144Updated 5 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆59Updated 3 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- POD-PINN code and manuscript☆51Updated 5 months ago
- Multifidelity DeepONet☆31Updated last year
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆40Updated 2 years ago
- ☆48Updated 3 years ago
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 2 years ago
- Easy Reduced Basis method☆84Updated 2 months ago