ebilionis / py-kle
Karhunen-Loeve Expansions for Gaussian Random Fields in Python
☆15Updated 10 years ago
Related projects ⓘ
Alternatives and complementary repositories for py-kle
- Machine learning of linear differential equations using Gaussian processes☆22Updated 6 years ago
- A Python module that implements tools for the simulation and identification of random fields using the Karhunen-Loeve expansion represent…☆20Updated 8 years ago
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 4 years ago
- ☆24Updated 6 years ago
- Deep Learning application to the partial differential equations☆29Updated 6 years ago
- ☆39Updated 4 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆23Updated 11 months ago
- ☆61Updated 5 years ago
- Tutorial on a number of topics in Deep Learning☆34Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆66Updated 4 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 4 years ago
- Adaptive multiphase flow through porous media☆28Updated 8 years ago
- ☆13Updated 8 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆82Updated 3 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆103Updated 4 years ago
- ☆37Updated last year
- Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"☆32Updated 5 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆45Updated 4 years ago
- Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).☆19Updated last year
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆17Updated 2 years ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- Tutorial on Gaussian Processes☆60Updated 4 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 3 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆18Updated last year
- ☆11Updated 3 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
- DeepONet extrapolation☆24Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆46Updated 3 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆9Updated last year
- Uncertainty Quantification in the POD-NN framework☆19Updated 4 years ago