maziarraissi / TutorialGP
Tutorial on Gaussian Processes
☆62Updated 4 years ago
Alternatives and similar repositories for TutorialGP:
Users that are interested in TutorialGP are comparing it to the libraries listed below
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 6 years ago
- Bayesian optimization and active learning with likelihood-weighted acquisition functions☆16Updated 7 months ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆37Updated 2 years ago
- ☆13Updated 3 years ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 7 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- ☆35Updated last year
- Compressive dynamic mode decomposition with control for compressive system identification☆38Updated 7 years ago
- Parametric Gaussian Process Regression for Big Data (Matlab Version)☆24Updated 6 years ago
- A MATLAB implementation of the co-kriging process using the DACE toolbox☆37Updated 7 years ago
- Polynomial Chaos Expansion Toolbox for MATLAB☆33Updated last year
- A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method☆79Updated last month
- Repository to tutorials on the implementation of the Transitional Ensemble Markov Chain Monte Carlo (TEMCMC) sampler for Bayesian Model U…☆17Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆62Updated 2 years ago
- ☆19Updated 3 years ago
- Multi-fidelity Gaussian Process☆25Updated 4 years ago
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆59Updated 8 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆55Updated 4 years ago
- ☆41Updated 7 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆62Updated 4 years ago
- ☆62Updated 5 years ago
- Data-driven reduced order modeling for nonlinear dynamical systems☆60Updated 2 months ago
- multifidelity global sensitivity analysis☆16Updated 2 years ago
- ☆21Updated 4 years ago
- Tutorials and examples of advanced sampling methods for solving Bayesian Model Updating Problems☆32Updated last year
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- Koopman Mode Decomposition☆71Updated 7 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆143Updated 4 years ago
- OpenCossan is an open and free toolbox for uncertainty quantification and management.☆51Updated last year