paraklas / GPTutorialLinks
A hands-on tutorial on supervised learning with Gaussian processes
☆37Updated 5 years ago
Alternatives and similar repositories for GPTutorial
Users that are interested in GPTutorial are comparing it to the libraries listed below
Sorting:
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- ☆63Updated 5 years ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 7 years ago
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆67Updated 8 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 4 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- ☆41Updated 5 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- 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
- ☆25Updated 7 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆25Updated last year
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- Tutorial on a number of topics in Deep Learning☆35Updated 5 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆43Updated 7 years ago
- Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …☆33Updated 4 years ago
- ☆116Updated 5 years ago
- Multi Fidelity Monte Carlo☆24Updated 5 years ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 5 years ago
- ☆21Updated 4 years ago
- ☆19Updated 3 years ago
- Deep Learning of Turbulent Scalar Mixing☆17Updated 5 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆57Updated 4 years ago
- Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurem…☆37Updated last year
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆106Updated 4 years ago
- Multi-fidelity Generative Deep Learning Turbulent Flows☆38Updated 4 years ago
- Bayesian optimized physics-informed neural network for parameter estimation☆32Updated 7 months ago
- Deep Learning application to the partial differential equations☆30Updated 7 years ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆20Updated 4 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 5 years ago