yifanc96 / NonLinPDEs-GPsolverLinks
Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes
☆40Updated 5 months ago
Alternatives and similar repositories for NonLinPDEs-GPsolver
Users that are interested in NonLinPDEs-GPsolver are comparing it to the libraries listed below
Sorting:
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- An integrated demo: Gaussian processes for PDEs and inverse problems☆16Updated 5 months ago
- ☆45Updated 3 years ago
- Source code for Deep Multigrid method https://arxiv.org/pdf/1711.03825.pdf☆19Updated 7 months ago
- ☆117Updated this week
- ☆42Updated 5 years ago
- An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.☆19Updated 2 months ago
- Pseudospectral Kolmogorov Flow Solver☆41Updated 2 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…☆26Updated last year
- ☆29Updated last year
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"☆50Updated last year
- Dimension reduced surrogate construction for parametric PDE maps☆38Updated 4 months ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆57Updated last year
- ☆54Updated 3 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- ☆15Updated 4 years ago
- Spectral Neural Operator☆78Updated 2 years ago
- A Python module that implements tools for the simulation and identification of random fields using the Karhunen-Loeve expansion represent…☆24Updated 9 years ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆20Updated 3 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆92Updated last month
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆39Updated last year
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆77Updated 2 months ago
- ☆12Updated 3 years ago
- Example problems in Physics informed neural network in JAX☆82Updated 2 years ago
- ☆25Updated 9 months ago
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆17Updated 2 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆31Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated last year
- PyTorch-FEniCS interface☆103Updated 4 years ago