mfschubert / sparsejac
Efficient forward- and reverse-mode sparse Jacobians using Jax
☆47Updated 8 months ago
Related projects ⓘ
Alternatives and complementary repositories for sparsejac
- Solve sparse linear systems in JAX using the KLU algorithm☆31Updated this week
- Differentiable interface to FEniCS for JAX☆50Updated 3 years ago
- A differentiable finite element analysis solver for structural optimization based on JAX☆21Updated last month
- ☆34Updated last year
- ☆11Updated 2 months ago
- The algorithmic differentation tool pyadjoint and add-ons.☆91Updated this week
- Numerical quadrature with JAX☆42Updated 2 weeks ago
- Automates adjoints. Forward and reverse mode algorithmic differentiation around implicit functions (not propagating AD through), as well …☆25Updated 4 months ago
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆89Updated 11 months ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆33Updated last week
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆55Updated this week
- Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling☆80Updated 3 years ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆20Updated 3 months ago
- A Julia library for hierarchical matrices☆40Updated last month
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆120Updated last month
- computational adjoint-based shape optimization and optimal control software for python☆52Updated this week
- ☆45Updated this week
- High-level model-order reduction to automate the acceleration of large-scale simulations☆37Updated this week
- An integrated demo: Gaussian processes for PDEs and inverse problems☆13Updated 5 months ago
- H2 Matrix Package☆24Updated last year
- Automatic Differentiation for Solid Mechanics☆54Updated 4 months ago
- Stiff Neural Ordinary Differential Equations☆30Updated last year
- GPU/TPU accelerated nonlinear least-squares curve fitting using JAX☆51Updated last year
- Material for workshop and autumn school on scientific machine learning 2023☆19Updated 10 months ago
- Easy interoperability with Automatic Differentiation libraries through NumPy interface to Firedrake and FEniCS☆14Updated 11 months ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆21Updated 6 months ago
- A fast direct solver for surface PDEs☆15Updated 4 months ago
- Bilinear interpolation on grids with jax☆12Updated 2 years ago
- No need to train, he's a smooth operator☆43Updated 6 months ago
- Interpolation and function approximation with JAX☆131Updated last week