timweiland / gp-fvmLinks
Probabilistic Finite Volume Method based on Affine Gaussian Process inference
☆11Updated last year
Alternatives and similar repositories for gp-fvm
Users that are interested in gp-fvm are comparing it to the libraries listed below
Sorting:
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 6 months ago
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11Updated 2 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆50Updated 4 months ago
- 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
- ☆10Updated 3 years ago
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆90Updated 2 weeks ago
- Gaussian processes with spherical harmonic features in JAX☆15Updated this week
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆52Updated 2 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆130Updated 11 months ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 4 months ago
- Matrix-free linear algebra in JAX.☆138Updated last week
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- Neural Emulator Architectures in JAX.☆18Updated 9 months ago
- The ✨Magical✨ JAX ML Library.☆17Updated 7 months ago
- ☆35Updated 2 years ago
- JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework☆72Updated 7 months ago
- Gradient-informed particle MCMC methods☆12Updated last year
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆40Updated 2 years ago
- Differentiable interface to FEniCS for JAX☆57Updated 4 years ago
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Updated 2 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆80Updated 3 months ago
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Updated 2 years ago
- Efficient Differentiable n-d PDE solvers in JAX.☆47Updated 9 months ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- ☆29Updated 2 years ago
- Literature and light wrappers for gaussian process models.☆48Updated 4 years ago
- Python package 'dgpsi' for deep and linked Gaussian process emulations☆27Updated 2 weeks ago
- A framework for composing Neural Processes in Python☆85Updated 8 months ago