Comprehensive notes and implementations from Monte Carlo Statistical Methods (2nd Ed.), focusing on Bayesian inference, filtering, smoothing, and state estimation using Monte Carlo and MCMC techniques.
machine-learning markov-chain statistical-inference monte-carlo-simulation bayesian-inference mcmc markov-chain-monte-carlo stochastic-processes probability-theory variance-reduction importance-sampling computational-statistics state-estimation-filters robotics-ai monte-carlo-statistical-methods
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Updated
Nov 26, 2025 - Jupyter Notebook