sequential-monte-carlo

baggepinnen/LowLevelParticleFilters.jl

State estimation, smoothing and parameter estimation using Kalman and particle filters.

kingaa/pomp

R package for statistical inference using partially observed Markov processes

tingiskhan/pyfilter

Particle filtering and sequential parameter inference in Python

FRBNY-DSGE/SMC.jl

Sequential Monte Carlo algorithm for approximation of posterior distributions.

TuringLang/AdvancedPS.jl

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

probcomp/GenParticleFilters.jl

Building blocks for simple and advanced particle filtering in Gen.

cyianor/smc2017

Collected code and materials from the intensive course preparing for the workshop on Sequential Monte Carlo (SMC) methods at Uppsala University, August 2017

mukeshramancha/transitional-mcmc

This repo contains the code of Transitional Markov chain Monte Carlo algorithm

OnlinePhylo/sts

Sequential Tree Sampler for online phylogenetics

christophmark/bayesianfridge

Sequential Monte Carlo sampler for PyMC2 models.

neuralyzer/pyabc

pyABC: distributed, likelihood-free inference

felixleopoldo/trilearn

Bayesian structure learning and classification in decomposable graphical models.

AdrienCorenflos/particle_mala

Gradient-informed particle MCMC methods

GrainLearning/grainLearning

A Bayesian uncertainty quantification toolbox for discrete and continuum numerical models of granular materials, developed by various projects of the University of Twente (NL), the Netherlands eScience Center (NL), University of Newcastle (AU), and Hiroshima University (JP).

miroslavradojevic/pnr

Automated Neuron Reconstruction from 3D Fluorescence Microscopy Images Using Sequential Monte Carlo Estimation

mooresm/serrsBayes

R package serrsBayes

amoretti86/phylo

Variational Combinatorial Sequential Monte Carlo methods for Bayesian Phylogenetic Inference

amoretti86/PSVO

Implementation of Particle Smoothing Variational Objectives

enceladus-rex/nasmc

An implementation of Neural Adaptive Sequential Monte Carlo (NASMC) using PyTorch

tlienart/SMC.jl

Sequential Monte Carlo methods in Julia (experimental)

biips/rbiips

R package for Bayesian inference with interacting particle systems

MauroCE/IntegratorSnippets

Code implementing Integrator Snippets, joint work with Christophe Andrieu and Chang Zhang

SeyedMuhammadHosseinMousavi/Synthetic-Data-Generation-by-Sequential-Monte-Carlo

Synthetic Data Generation by Sequential Monte Carlo (SMC)

alessandro-viani/ToyExample

Example of an inverse problem where the aim is to reconstruct the parameters of an unknown number of weighted Gaussian function

ocbe-uio/elfi

A Python package for likelihood-free inference (LFI) methods such as Approximate Bayesian Computation (ABC)

biips/matbiips

Matlab toolbox for Bayesian inference with interacting particle systems

charlesknipp/sequential_monte_carlo

This module is an efficient and flexible implementation of various Sequential Monte Carlo (SMC) methods. Bayesian updates occur for both latent states and model parameters using joint inference.

i-am-sorri/SESAME_core

jackanth/bethe-faster

A framework for particle identification and energy estimation using a sequential Monte Carlo method

jzhou316/SMC-KP

Sequential Monte Carlo for Kinetic Prediction of Time-Varying Data Generating Processes

manuvazquez/smc_tools

Sequential Monte Carlo Tools

MCS-Quantum/seabed

SEquential Analysis and Bayesian Experimental Design (SEABED) powered by JAX

miroslavradojevic/phdthesis

PhD dissertation: Methods for Automated Neuron Image Analysis candidate: Miroslav Radojevic Publisher: Erasmus University ISBN 978-94-6361-204-3

voduchuy/StMcmcCme

This repository contains the Python modules and scripts to reproduce the results in the paper "Catanach, Vo, Munsky. IJUQ 2020."

zcaiElvis/SMCRejuvenation

Lightweight Metropolis Hasting as a rejuvenation procedures for particles in Sequential Monte Carlo. Inference in Higher Order Probabilistic Languages with Pytorch