Xiao-dong-Wang / Multifidelity-GPLinks
Multi-fidelity Gaussian Process
☆27Updated 4 years ago
Alternatives and similar repositories for Multifidelity-GP
Users that are interested in Multifidelity-GP are comparing it to the libraries listed below
Sorting:
- ☆38Updated 2 years ago
- ☆42Updated 2 years ago
- Multi-fidelity regression with neural networks☆15Updated 9 months ago
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆32Updated 4 years ago
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆67Updated 8 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
- ☆63Updated 6 years ago
- multi-fidelity neural network☆20Updated 2 years ago
- Multi-fidelity probability machine learning☆18Updated 7 months ago
- Pytorch implementation of Bayesian physics-informed neural networks☆63Updated 4 years ago
- ☆14Updated 3 years ago
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- Multi-fidelity reduced-order surrogate modeling☆25Updated 3 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆13Updated 9 months ago
- Multi-fidelity classification with Gaussian process☆17Updated 2 years ago
- multifidelity global sensitivity analysis☆17Updated 3 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆107Updated 5 years ago
- Research/development of physics-informed neural networks for dynamic systems☆29Updated 9 months ago
- A MATLAB implementation of the co-kriging process using the DACE toolbox☆39Updated 8 years ago
- This repository comprises Jupyter Notebooks that serve as supplementary material to the journal article titled "Review of Multifidelity M…☆10Updated last year
- Codes related to our paper "Sparse Polynomial Chaos Expansions via D-optimal Designs and Compressed Sensing." https://www.sciencedirect.…☆20Updated 6 years ago
- ☆11Updated 4 years ago
- Boosting the training of physics informed neural networks with transfer learning☆26Updated 4 years ago
- A Matlab toolbox for stochastic response analysis by DR-PDEE/GE-GDEE☆26Updated last year
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆10Updated 5 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
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 3 years ago
- an active-learning method for reliability analysis based on multi-fidelity kriging model☆38Updated last year
- Multifidelity Kriging, Efficient Global Optimization☆18Updated 6 years ago