dubourg / python-randomfieldsLinks
A Python module that implements tools for the simulation and identification of random fields using the Karhunen-Loeve expansion representation.
☆24Updated 9 years ago
Alternatives and similar repositories for python-randomfields
Users that are interested in python-randomfields are comparing it to the libraries listed below
Sorting:
- Generator of 2D gaussian random fields☆52Updated 3 years ago
- DeepGreen network written in Tensorflow 2☆30Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆63Updated 6 years ago
- Machine learning of linear differential equations using Gaussian processes☆25Updated 7 years ago
- ☆42Updated 5 years ago
- ☆14Updated 4 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Dimension reduced surrogate construction for parametric PDE maps☆38Updated 3 months ago
- ☆49Updated 2 years ago
- Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms☆12Updated last year
- ☆23Updated last year
- NodeLab is a simple MATLAB-repository for node-generation and adaptive refinement for testing, and implementing various meshfree methods …☆32Updated 10 months ago
- Multi-fidelity reduced-order surrogate modeling☆28Updated 5 months ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- PyTorch-FEniCS interface☆103Updated 4 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆39Updated 4 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆89Updated 4 years ago
- ☆32Updated 3 years ago
- ☆39Updated last year
- ☆39Updated 2 years ago
- Application of Graph Neural Networks to predict material properties from their microstructures.☆19Updated last year
- ☆26Updated 7 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Updated 2 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆147Updated 5 years ago
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆129Updated 2 weeks ago
- ☆12Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago