MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
☆342Dec 7, 2022Updated 3 years ago
Alternatives and similar repositories for sampyl
Users that are interested in sampyl are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Manifold Markov chain Monte Carlo methods in Python☆238Jul 20, 2026Updated 3 weeks ago
- Hamiltonain Monte Carlo in Python☆40Nov 7, 2019Updated 6 years ago
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆139Dec 1, 2020Updated 5 years ago
- Just a little MCMC☆235Jun 25, 2024Updated 2 years ago
- Approximate Bayesian Computation Sequential Monte Carlo sampler for parameter estimation.☆39Mar 20, 2020Updated 6 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆426Mar 21, 2024Updated 2 years ago
- Efficiently computes derivatives of NumPy code.☆7,522Aug 10, 2026Updated last week
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Jun 7, 2018Updated 8 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆87May 8, 2020Updated 6 years ago
- Look Ahead Hamiltonian Monte Carlo☆31Mar 29, 2015Updated 11 years ago
- A probabilistic programming language in TensorFlow. Deep generative models, variational inference.☆4,844Mar 18, 2024Updated 2 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Dec 7, 2016Updated 9 years ago
- Documentation:☆132May 22, 2023Updated 3 years ago
- Tensorflow implementation of Stein Variational Gradient Descent (SVGD)☆26Jan 13, 2018Updated 8 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Bayesian dessert for Lasagne☆83Jun 25, 2017Updated 9 years ago
- Interactive Markov-chain Monte Carlo Javascript demos☆936Jan 22, 2026Updated 6 months ago
- Notas del curso de Simulación☆13Feb 3, 2026Updated 6 months ago
- Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.☆333Mar 20, 2024Updated 2 years ago
- Pure Python, MIT-licensed implementation of nested sampling algorithms for evaluating Bayesian evidence.☆76Oct 7, 2025Updated 10 months ago
- Pseudo-Marginal Slice Sampling☆19Jun 8, 2016Updated 10 years ago
- BAyesian Model-Building Interface (Bambi) in Python.☆1,294Updated this week
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆1,109Updated this week
- ⚡️ zeus: Lightning Fast MCMC ⚡️☆243Feb 18, 2024Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- modular implementation of new algorithm☆13Jun 4, 2014Updated 12 years ago
- Fast and flexible Gaussian Process regression in Python☆461Jun 22, 2026Updated last month
- A kernel-density-based, embarrassingly parallel ensemble sampler☆36Jul 9, 2022Updated 4 years ago
- ☆32Oct 29, 2025Updated 9 months ago
- Bayesian Modeling and Probabilistic Programming in Python☆9,710Updated this week
- Supplementary Material to accompany the paper, DJ Warne, SA Sisson, C Drovandi (2019) Acceleration of expensive computations in Bayesian…☆13Oct 23, 2020Updated 5 years ago
- The Python ensemble sampling toolkit for affine-invariant MCMC☆1,597Aug 10, 2026Updated last week
- A web interface for exploring PyMC3 traces☆45Feb 14, 2018Updated 8 years ago
- Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.☆2,737Updated this week
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Feb 9, 2017Updated 9 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆210Aug 25, 2016Updated 9 years ago
- Decorator for PyMC3☆50Jun 11, 2021Updated 5 years ago
- Exploratory analysis of Bayesian models with Python☆1,845Aug 11, 2026Updated last week
- ☆116Nov 7, 2022Updated 3 years ago
- Code to accompany the paper "Fast Hamiltonian Monte Carlo Using GPU Computing"☆37Nov 3, 2016Updated 9 years ago
- Dynamic Nested Sampling package for computing Bayesian posteriors and evidences☆421Aug 8, 2026Updated last week