Sequential Monte Carlo in python
Particle Gibbs-based optimal control with performance guarantees for unknown systems with latent states
Sequential Monte Carlo methods for Continuous-Discrete State Space Models
We propose a particle MCMC sampler to learn the kinetic parameters of a chemical system, specifically the adsorption and desorption of CO on Pd(111).
Sequential Monte Carlo methods for Elixir — Bootstrap Particle Filter, PMCMC, Online SMC². Streaming Bayesian inference on the BEAM.
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