marvinpfoertner / linpde-gpLinks
Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"
☆32Updated last year
Alternatives and similar repositories for linpde-gp
Users that are interested in linpde-gp are comparing it to the libraries listed below
Sorting:
- Matrix-free linear algebra in JAX.☆153Updated last month
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated last month
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 11 months ago
- Efficient Differentiable n-d PDE solvers in JAX.☆52Updated 2 months ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆131Updated this week
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆121Updated 3 weeks ago
- Neural Emulator Architectures in JAX.☆23Updated last year
- ☆117Updated this week
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated last year
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆43Updated 2 years ago
- Efficient forward- and reverse-mode sparse Jacobians using Jax☆68Updated last month
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆107Updated 2 years ago
- Kolmogorov-Arnold Networks built on JAX☆93Updated 3 weeks ago
- A software package for flexible HPC GPs☆15Updated 3 weeks ago
- ☆18Updated last year
- An integrated demo: Gaussian processes for PDEs and inverse problems☆16Updated 5 months ago
- Interpolation and function approximation with JAX☆235Updated this week
- Differentiable interface to FEniCS for JAX☆58Updated 4 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆94Updated 2 months ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆40Updated 5 months ago
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆290Updated last year
- ☆52Updated this week
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 8 months ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆60Updated 3 years ago
- Quasi-Monte Carlo point generators, automatic transformations, and adaptive stopping criteria☆77Updated this week
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high perf…☆235Updated 3 years ago
- ☆28Updated 3 years ago