nchopin / particlesLinks
Sequential Monte Carlo in python
☆474Updated last month
Alternatives and similar repositories for particles
Users that are interested in particles are comparing it to the libraries listed below
Sorting:
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆240Updated last year
- Gaussian processes in JAX and Flax.☆558Updated last week
- A Python package for probabilistic state space modeling with JAX☆887Updated 4 months ago
- Probabilistic Numerics in Python.☆459Updated 5 months ago
- Gaussian process modelling in Python☆225Updated 11 months ago
- Multi-Output Gaussian Process Toolkit☆184Updated 6 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Manifold Markov chain Monte Carlo methods in Python☆236Updated last week
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆977Updated 2 weeks ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆465Updated last year
- sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you nee…☆757Updated this week
- Particle filtering and sequential parameter inference in Python☆83Updated 2 years ago
- Structural Time Series in JAX☆203Updated last year
- Just a little MCMC☆232Updated last year
- Example codes for the book Applied Stochastic Differential Equations☆200Updated last month
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Statistical Rethinking (2nd ed.) with NumPyro☆464Updated 7 months ago
- ☆155Updated 3 years ago
- State of the art inference for your bayesian models.☆231Updated 7 months ago
- The tiniest of Gaussian Process libraries☆327Updated 3 weeks ago
- Probabilistic Inference on Noisy Time Series☆239Updated 2 months ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Numerical integration of Ito or Stratonovich SDEs☆167Updated 2 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Simulation-based inference benchmark☆106Updated 10 months ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆286Updated 4 years ago
- Large-scale, multi-GPU capable, kernel solver☆192Updated 4 months ago
- GPstuff - Gaussian process models for Bayesian analysis☆175Updated 2 years ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆458Updated 2 months ago