Random Notes
Probability Essentials
- Kernel Density Estimation
- Convergence notions
Discrete-time Markov chains
- Essential definitions
- Invariant distributions
- Countable-space Markov chains
- Continuous-space Markov chains
  - Irreducibility and recurrence in the continuous-space case
Sampling methods
- Overview
- Random number generators
- Transform methods
  - Probability integral transform
  - Box-Muller transform
- Accept-Reject methods
  - Rejection sampling
  - Empirical supremum rejection sampling
- Markov Chain Monte Carlo (MCMC)
- Langevin sampling
Bayesian inference
Generative models
- Score matching
Sensitivity analysis
- Overview

Version

Sampling methods
Markov Chain Monte Carlo (MCMC)
Gibbs sampling

Gibbs sampling

Gibbs sampling

« Convergence of Metropolis-Hastings Hamiltonian Monte Carlo (HMC) »

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