Sequential Monte Carlo in python
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Updated
Jul 25, 2024 - Python
Sequential Monte Carlo in python
Particle filtering and sequential parameter inference in Python
This repo contains the code of Transitional Markov chain Monte Carlo algorithm
Sequential Monte Carlo sampler for PyMC2 models.
Bayesian structure learning and classification in decomposable graphical models.
Gradient-informed particle MCMC methods
Variational Combinatorial Sequential Monte Carlo methods for Bayesian Phylogenetic Inference
Implementation of Particle Smoothing Variational Objectives
An implementation of Neural Adaptive Sequential Monte Carlo (NASMC) using PyTorch
Code implementing Integrator Snippets, joint work with Christophe Andrieu and Chang Zhang
A Python package for likelihood-free inference (LFI) methods such as Approximate Bayesian Computation (ABC)
SEquential Analysis and Bayesian Experimental Design (SEABED) powered by JAX
A variation of Pacman arcade game designed to train Pacman agents that use sensors to locate and eat invisible ghosts with phenomenal efficiency. Used Joint Particle Filter algorithm in AI to get 30% optimized results.
Workshop for A Corunha in MCTS
Code for the paper "Backward importance sampling for online estimation of state space models"
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