probabilistic-numerics / probnum-spring-schoolLinks
Tutorial materials of the Probabilistic Numerics Spring School.
☆35Updated 2 years ago
Alternatives and similar repositories for probnum-spring-school
Users that are interested in probnum-spring-school are comparing it to the libraries listed below
Sorting:
- Matrix-free linear algebra in JAX.☆148Updated last week
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 9 months ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated this week
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆116Updated last week
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆42Updated 2 years ago
- A generic interface for linear algebra backends☆75Updated 2 weeks ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 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…☆21Updated last year
- Code for Gaussian Score Matching Variational Inference☆35Updated 8 months ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 6 months ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆51Updated 3 months ago
- Laplace approximations in JAX.☆37Updated last week
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Zonal Spherical Harmonics in d Dimensions in TensorFlow, PyTorch and Jax☆34Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 5 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Simulation-based inference benchmark☆106Updated 9 months ago
- ☆198Updated 2 weeks ago
- Normalizing Flows using JAX☆85Updated last year
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆240Updated last year
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 5 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 11 months ago
- Simulation-based inference in JAX☆39Updated 7 months ago
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆222Updated last year
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Updated 3 years ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- Sketched linear operations for PyTorch☆97Updated 3 weeks ago
- Riemannian Optimization Using JAX☆53Updated 2 years ago