AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
☆39Oct 23, 2023Updated 2 years ago
Alternatives and similar repositories for aemcmc
Users that are interested in aemcmc are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- An HMC/NUTS implementation in Aesara☆31Jun 22, 2023Updated 3 years ago
- Tools for an Aesara-based PPL.☆67Oct 28, 2024Updated last year
- Sampling with Blackjax on Aesara☆11Mar 10, 2023Updated 3 years ago
- An efficient and flexible sampler of the Pólya-Gamma distribution with a NumPy/SciPy compatible interface.☆28Apr 20, 2025Updated last year
- Tutorials and sampling algorithm comparisons☆86Updated this week
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arra…☆1,218Nov 15, 2024Updated last year
- Hidden Markov models in PyMC3☆96Mar 20, 2024Updated 2 years ago
- A backend for storing MCMC draws.☆22Jun 22, 2026Updated 3 weeks ago
- Exponential families for JAX☆77Updated this week
- Differentiable interface to FEniCS for PyMC3☆21Nov 28, 2022Updated 3 years ago
- ☆18Jan 5, 2023Updated 3 years ago
- It's interpreters all the way down.☆13May 12, 2021Updated 5 years ago
- ☆30Jul 10, 2026Updated last week
- Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.☆333Mar 20, 2024Updated 2 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Python codes for Sequential Monte Carlo sampling Technique. This technique is robust in sampling close to 1000-D posterior probability de…☆17Sep 13, 2023Updated 2 years ago
- ☆16May 30, 2023Updated 3 years ago
- Reference implementation of algorithms for reinforcement learning and Markov decision processes.☆12Jan 28, 2021Updated 5 years ago
- Bayesian inference for a logistic regression model in various languages☆43Jul 12, 2023Updated 3 years ago
- Numba compatible SCFG (Structured Control Flow Graphs) utilities.☆29Updated this week
- A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.☆59Jul 25, 2024Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆106Oct 23, 2023Updated 2 years ago
- Gradient-informed particle MCMC methods☆12Jan 29, 2024Updated 2 years ago
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆319Jul 8, 2026Updated last week
- 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.
- An implementation of the Zarr storage format specification for chunked & compressed multidimensional arrays.☆26Apr 22, 2025Updated last year
- This is a Pytorch implementation of [normalizing flows on tori and spheres, ICML 2020]☆19Oct 12, 2022Updated 3 years ago
- A general purpose Gaussian process regression module☆11Jun 20, 2026Updated last month
- Gaussian processes in JAX and Equinox.☆639Updated this week
- volcanic source model and inversion framework in python☆23Apr 22, 2026Updated 2 months ago
- Code and Notebooks for Yang et al. (2024) on InSAR tropospheric correction based on local texture correlation☆15Nov 7, 2024Updated last year
- PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python☆131Jul 1, 2026Updated 2 weeks ago
- Credit Default Swaps in R☆13Sep 13, 2017Updated 8 years ago
- Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.☆65Mar 20, 2024Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Probabilistic programming with large language models☆176Jun 7, 2026Updated last month
- Straightforward unification in Python that's extensible via generic functions.☆53Feb 25, 2026Updated 4 months ago
- Powerful add-ons for PyMC☆142Updated this week
- Full moment tensor inversion using Hamiltonian Monte Carlo (HMC) sampling☆15Feb 11, 2025Updated last year
- Implementation of Gibbs sampling for spike and slab priors☆19Mar 1, 2017Updated 9 years ago
- ☆16Apr 8, 2025Updated last year
- Plot with matplotlib using ATLAS style☆12Jun 23, 2020Updated 6 years ago