Uncertainty quantification with PyTorch
☆378Jan 27, 2026Updated last month
Alternatives and similar repositories for posteriors
Users that are interested in posteriors are comparing it to the libraries listed below
Sorting:
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆1,021Feb 3, 2026Updated 3 weeks ago
- Gaussian Markov Random Fields (GMRFs) and Integrated Nested Laplace Approximation (INLA)☆22Apr 17, 2024Updated last year
- Exact OU processes with JAX☆59Jan 6, 2026Updated last month
- A Python package for probabilistic state space modeling with JAX☆929Jan 6, 2026Updated last month
- State of the art inference for your bayesian models.☆233Jan 14, 2026Updated last month
- Laplace approximations for Deep Learning.☆533Apr 22, 2025Updated 10 months ago
- Compositional Linear Algebra☆507Aug 1, 2025Updated 7 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆467Aug 28, 2024Updated last year
- Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax☆516Updated this week
- The tiniest of Gaussian Process libraries☆333Feb 8, 2026Updated 2 weeks ago
- A Library for Uncertainty Quantification.☆922Apr 23, 2025Updated 10 months ago
- Gaussian processes in JAX and Flax.☆593Feb 20, 2026Updated last week
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Dec 22, 2023Updated 2 years ago
- A probabilistic programming framework☆45Feb 17, 2026Updated last week
- 🧱 Modula software package☆321Aug 18, 2025Updated 6 months ago
- A Simple Statistical Distribution Library in JAX☆16Mar 30, 2024Updated last year
- General framework for Bayesian inversion of continuous hierarchical models☆10Sep 20, 2021Updated 4 years ago
- Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/☆2,792Updated this week
- Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.☆2,610Updated this week
- A JAX research toolkit for building, editing, and visualizing neural networks.☆1,869Jun 22, 2025Updated 8 months ago
- Probabilistic Numerics in Python.☆459Jul 3, 2025Updated 7 months ago
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,912Updated this week
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆302Updated this week
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆544Feb 16, 2026Updated last week
- Structural Time Series in JAX☆214May 8, 2024Updated last year
- ☆43May 3, 2024Updated last year
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆43Apr 12, 2023Updated 2 years ago
- Sampling with Blackjax on Aesara☆11Mar 10, 2023Updated 2 years ago
- Hardware accelerated, batchable and differentiable optimizers in JAX.☆1,027Dec 17, 2025Updated 2 months ago
- Tools for an Aesara-based PPL.☆67Oct 28, 2024Updated last year
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆700Feb 5, 2026Updated 3 weeks ago
- State-space model inference with JAX☆48Updated this week
- Turn SymPy expressions into trainable JAX expressions.☆362Feb 4, 2026Updated 3 weeks ago
- Gaussian process modelling in Python☆226Dec 15, 2024Updated last year
- Tutorials and sampling algorithm comparisons☆80Updated this week
- Quantification of Uncertainty with Adversarial Models☆29Jul 11, 2023Updated 2 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆35May 10, 2023Updated 2 years ago
- Normalizing-flow enhanced sampling package for probabilistic inference in Jax☆255Oct 28, 2025Updated 4 months ago
- ☆60Mar 8, 2022Updated 3 years ago