yifanc96 / GaussianProcessPDEsLinks
An integrated demo: Gaussian processes for PDEs and inverse problems
☆16Updated 6 months ago
Alternatives and similar repositories for GaussianProcessPDEs
Users that are interested in GaussianProcessPDEs are comparing it to the libraries listed below
Sorting:
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆40Updated 6 months ago
- ☆10Updated 2 months ago
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆17Updated 2 years ago
- Practicum on Supervised Learning in Function Spaces☆34Updated 3 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆28Updated last year
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Stiff Neural Ordinary Differential Equations☆35Updated 2 years ago
- ☆29Updated last year
- ☆44Updated 3 years ago
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆79Updated 3 weeks ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆58Updated last year
- Code for ResDMD: data-driven spectral properties of Koopman Operators☆42Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated 2 years ago
- Update PDEKoopman code to Tensorflow 2☆24Updated 4 years ago
- Pseudospectral Kolmogorov Flow Solver☆42Updated 2 years ago
- Source code for Deep Multigrid method https://arxiv.org/pdf/1711.03825.pdf☆19Updated 9 months ago
- ☆32Updated last year
- Differentiable interface to FEniCS for JAX☆58Updated 4 years ago
- ☆117Updated this week
- Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).☆19Updated 2 years ago
- Dimension reduced surrogate construction for parametric PDE maps☆39Updated 5 months ago
- Material for workshop and autumn school on scientific machine learning 2023☆21Updated 2 years ago
- ☆42Updated 5 years ago
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆291Updated last year
- Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling☆87Updated 4 years ago
- Efficient Differentiable n-d PDE solvers in JAX.☆52Updated this week
- ☆18Updated last year
- Code for the paper "Generative AI for fast and accurate statistical computation of fluids"☆48Updated 6 months ago
- ☆21Updated 5 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆61Updated 3 years ago