bsciolla / gaussian-random-fieldsLinks
Generator of 2D gaussian random fields
☆51Updated 3 years ago
Alternatives and similar repositories for gaussian-random-fields
Users that are interested in gaussian-random-fields are comparing it to the libraries listed below
Sorting:
- A Python module that implements tools for the simulation and identification of random fields using the Karhunen-Loeve expansion represent…☆24Updated 9 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆39Updated 2 years ago
- ☆44Updated 2 years ago
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆116Updated 2 months ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆14Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- ☆49Updated last year
- ☆63Updated 6 years ago
- A library for dimensionality reduction on spatial-temporal PDE☆67Updated last year
- Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration☆16Updated last year
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- ☆37Updated 2 years ago
- ☆38Updated last year
- Pseudospectral Kolmogorov Flow Solver☆40Updated last year
- Repository for sharing code and data assocaited with En-DeepONet architecture☆35Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- ☆106Updated last year
- ☆116Updated 6 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆83Updated last month
- Machine learning of linear differential equations using Gaussian processes☆23Updated 7 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…☆42Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- Solving PDEs with NNs☆55Updated 2 years ago
- ☆26Updated 7 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- ☆54Updated 3 years ago
- Gaussian process-based interpretable latent space dynamics identification through deep autoencoder☆35Updated last week