sbi-dev / sbiLinks
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.
☆757Updated this week
Alternatives and similar repositories for sbi
Users that are interested in sbi are comparing it to the libraries listed below
Sorting:
- Gaussian processes in JAX and Flax.☆561Updated this week
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆977Updated 2 weeks ago
- A Python package for probabilistic state space modeling with JAX☆889Updated this week
- Probabilistic Numerics in Python.☆459Updated 5 months ago
- The tiniest of Gaussian Process libraries☆327Updated this week
- Community-sourced list of papers and resources on neural simulation-based inference.☆137Updated last month
- A Python library for amortized Bayesian workflows using generative neural networks.☆622Updated this week
- Simulation-based inference benchmark☆106Updated 10 months ago
- Sequential Monte Carlo in python☆474Updated last month
- Normalizing-flow enhanced sampling package for probabilistic inference in Jax☆253Updated last month
- ☆203Updated last month
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆465Updated last year
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆75Updated 5 months ago
- Probabilistic Inference on Noisy Time Series☆239Updated 2 months ago
- Likelihood-free AMortized Posterior Estimation with PyTorch☆131Updated last year
- Statistical Rethinking (2nd ed.) with NumPyro☆464Updated 7 months ago
- Manifold Markov chain Monte Carlo methods in Python☆236Updated last week
- State of the art inference for your bayesian models.☆231Updated 7 months ago
- A system for scientific simulation-based inference at scale.☆164Updated last year
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated last year
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆676Updated last week
- Just a little MCMC☆232Updated last year
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆504Updated 3 weeks ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Normalizing flows in PyTorch☆425Updated last month
- Bayesian learning and inference for state space models☆661Updated 6 months ago
- Probabilistic Programming and Nested sampling in JAX☆212Updated 2 weeks ago
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,845Updated 2 months ago
- SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory☆23Updated 2 years ago
- Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax☆492Updated this week