the prior distribution for probabilistic numerical methods
-
Updated
Jul 30, 2020 - Jupyter Notebook
the prior distribution for probabilistic numerical methods
Python tools for solving data-constrained finite element problems
Information and materials for Google Summer of Code participants developing for ProbNum.
Evaluate the accuracy, efficiency, and uncertainty-calibration of probabilistic numerical algorithms.
Published asv benchmark reports and database of ProbNum.
Various probabilistic numerics projects. Main one is Laplace_Approximation.
Probabilistic ODE solvers are fun, but are they fast?
Probabilistic Linear Solvers for Machine Learning (NeurIPS 2020)
IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
Numerical Integration Methods and Probabilistic Methods for generating random numbers.
Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and with out-of-the-box uncertainty quantification.
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.
Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.
Website of the Probabilistic Numerics community.
Physics-Enhanced Regression for Initial Value Problems
Practical session on implementing probabilistic linear solvers at the Probabilistic Numerics Spring School 2024
Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"
Probabilistic Numerics in Python.
Computation-Aware Kalman Filtering and RTS Smoothing
Code for the paper "Computation-Aware Kalman Filtering and Smoothing"
Add a description, image, and links to the probabilistic-numerics topic page so that developers can more easily learn about it.
To associate your repository with the probabilistic-numerics topic, visit your repo's landing page and select "manage topics."