paraklas / GPTutorial
A hands-on tutorial on supervised learning with Gaussian processes
☆36Updated 5 years ago
Alternatives and similar repositories for GPTutorial:
Users that are interested in GPTutorial are comparing it to the libraries listed below
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆59Updated 8 years ago
- ☆62Updated 5 years ago
- 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
- Tutorial on Gaussian Processes☆62Updated 4 years ago
- ☆40Updated 4 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- Tutorial on a number of topics in Deep Learning☆34Updated 4 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆41Updated 6 years ago
- Deep Learning of Turbulent Scalar Mixing☆16Updated 5 years ago
- Parametric Gaussian Process Regression for Big Data (Matlab Version)☆24Updated 6 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆62Updated 4 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 4 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- ☆24Updated 6 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 4 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…☆38Updated last year
- 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 application to the partial differential equations☆30Updated 6 years ago
- ☆35Updated last year
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆46Updated 6 years ago
- Uncertainty Quantification in the POD-NN framework☆19Updated 4 years ago
- ☆17Updated 4 years ago
- POD-PINN code and manuscript☆47Updated 2 months ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆143Updated 4 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆105Updated 4 years ago
- ☆8Updated 4 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 6 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆32Updated last year