Random Notes
Probability Essentials
- Kernel Density Estimation
Discrete-time Markov chains
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

Discrete-time Markov chains
Convergence notions

Convergence notions

Convergence notions

Weak convergence

Strong convergence

Total variation norm

Weiserstein distance

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