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.
☆713Updated 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.☆524Updated last month
- The tiniest of Gaussian Process libraries☆313Updated 3 weeks ago
- A Python package for probabilistic state space modeling with JAX☆847Updated 3 weeks ago
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆937Updated 3 months ago
- A Python library for amortized Bayesian workflows using generative neural networks.☆586Updated this week
- Normalizing-flow enhanced sampling package for probabilistic inference in Jax☆249Updated last month
- Community-sourced list of papers and resources on neural simulation-based inference.☆121Updated 2 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆454Updated 11 months ago
- Simulation-based inference benchmark☆99Updated 6 months ago
- Probabilistic Numerics in Python.☆454Updated last month
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆69Updated last month
- Sequential Monte Carlo in python☆462Updated last month
- Likelihood-free AMortized Posterior Estimation with PyTorch☆130Updated 11 months ago
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆625Updated last week
- ☆178Updated 3 weeks ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆234Updated last year
- Manifold Markov chain Monte Carlo methods in Python☆232Updated last month
- A system for scientific simulation-based inference at scale.☆164Updated last year
- State of the art inference for your bayesian models.☆220Updated 3 months ago
- Bayesian learning and inference for state space models☆641Updated 2 months ago
- Just a little MCMC☆227Updated last year
- Normalizing flows in PyTorch☆401Updated last month
- Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.☆106Updated this week
- ⚡️ zeus: Lightning Fast MCMC ⚡️☆238Updated last year
- Probabilistic Inference on Noisy Time Series☆238Updated 5 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 9 months ago
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆450Updated 3 weeks ago
- Statistical Rethinking (2nd ed.) with NumPyro☆461Updated 3 months ago
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,704Updated this week
- SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory☆23Updated 2 years ago