pnkraemer

tueplots

Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other scientific publications.

probdiffeq

Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and custom information operators. Compatible with the broader JAX scientific computing ecosystem.

tornadox

Probabilistic ODE solvers are fun, but are they fast?

matfree

Matrix-free linear algebra in JAX.

diffeqzoo

A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiological models, IVPs, BVPs, and more.

probfindiff

Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and with out-of-the-box uncertainty quantification.

million-dimension-prob-ode-solver-experiments

differentiable_likelihoods

Differentiable likelihoods for fast inversion of likelihood-free dynamical systems

probabilistic-bvp-solver

mini-stochastic-interpolants

gp-emulators

A small collection of python-scripts associated with Gaussian process emulators in Bayesian inverse problems

rbf-tools

A small collection of functions associated with radial basis function interpolation and collocation

awesome-jax

JAX - A curated list of resources https://github.com/google/jax

H2Lib

H2Lib public repository

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

mpl-third-party

Webpage

pnkraemer.github.io

probnum

Probabilistic Numerics in Python.

probnum-evaluation

Evaluate probabilistic numerical algorithms.

probnum-spring-school

Tutorial materials of the Probabilistic Numerics Spring School.

ProbNumDiffEq.jl

Probabilistic ODE Solvers via Bayesian Filtering and Smoothing

PSDMatrices.jl

Positive semi-definite matrix types in Julia

sampling-book

Tutorials and sampling algorithm comparisons

stochman

Algorithms for computations on random manifolds made easier