AaltoML / BayesNewton
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
☆232Updated last year
Alternatives and similar repositories for BayesNewton:
Users that are interested in BayesNewton are comparing it to the libraries listed below
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- Deep GPs built on top of TensorFlow/Keras and GPflow☆124Updated 5 months ago
- Gaussian processes in JAX.☆489Updated this week
- Gaussian process modelling in Python☆222Updated 3 months ago
- State of the art inference for your bayesian models.☆204Updated 3 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- ☆152Updated 3 weeks ago
- ☆151Updated 2 years ago
- Structural Time Series in JAX☆188Updated 10 months ago
- Minimal Implementation of Bayesian Optimization in JAX☆90Updated 2 months ago
- The tiniest of Gaussian Process libraries☆307Updated 2 weeks ago
- A generic interface for linear algebra backends☆73Updated last month
- Simulation-based inference benchmark☆96Updated 2 months ago
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆251Updated last week
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆107Updated 3 weeks ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆26Updated 7 months ago
- Solve ODEs fast, with support for PyMC☆112Updated 10 months ago
- Tutorials and sampling algorithm comparisons☆72Updated this week
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆392Updated last week
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Just a little MCMC☆223Updated 9 months ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆30Updated 8 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆63Updated 2 months ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆58Updated 11 months ago
- Probabilistic Numerics in Python.☆448Updated 11 months ago