chi-feng / gp-demoLinks
Gaussian Process Regression Interactive Javascript Demo
☆55Updated 6 years ago
Alternatives and similar repositories for gp-demo
Users that are interested in gp-demo are comparing it to the libraries listed below
Sorting:
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Solve ODEs fast, with support for PyMC☆114Updated last year
- Just a little MCMC☆227Updated last year
- ABCpy package☆114Updated last year
- Turning SymPy expressions into JAX functions☆45Updated 4 years ago
- A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.☆57Updated 11 months ago
- Differentiable interface to FEniCS for PyMC3☆20Updated 2 years ago
- All things Monte Carlo, written in JAX.☆31Updated 2 years ago
- probabilistic programming focused on fun☆41Updated 8 months ago
- Simulation-based inference benchmark☆97Updated 5 months ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Probabilistic Programming and Nested sampling in JAX☆184Updated 2 weeks ago
- Exponential families for JAX☆71Updated this week
- Manifold Markov chain Monte Carlo methods in Python☆230Updated 2 weeks ago
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆132Updated 4 years ago
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆41Updated 2 years ago
- Conditional density estimation with neural networks☆31Updated 5 months ago
- Unbiased MCMC with couplings☆19Updated 5 years ago
- A generic interface for linear algebra backends☆73Updated 3 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- A Python toolkit for (simulation-based) inference and the mechanization of science.☆53Updated 3 years ago
- A simple library to run variational inference on Stan models.☆32Updated 2 years ago
- Approximate Bayesian Computation Sequential Monte Carlo sampler for parameter estimation.☆40Updated 5 years ago
- pyrff: Python implementation of random fourier feature approximations for gaussian processes☆28Updated 3 months ago
- A software package for flexible HPC GPs☆16Updated this week
- Minimal Implementation of Bayesian Optimization in JAX☆95Updated 2 months ago
- Matrix-free linear algebra in JAX.☆125Updated last month
- A list of Python-based MCMC & ABC packages☆123Updated 2 weeks ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆233Updated last year
- AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.☆39Updated last year