Mathematics for AI and Machine Learning

Foundations for modern AI and machine learning

Density Evolution

Chapter 19 Dynamics & diffusion

Chapter 19: Stochastic Differential Equations — Probability Evolution (also appears in Ch. 21, Ch. 21)

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From the book

Chapter 19: Stochastic Differential Equations. In the chapter mind map this icon labels Probability Evolution: Fokker-Planck Preview. The discussion below is excerpted and lightly edited from § Probability Evolution Viewpoint in Mathematics for AI and Machine Learning. Related material also appears in Chapter 21 (Paths vs Densities: Three Levels of Description), Chapter 21 (Determinism of Prob Distributions).

  • A path distribution
  • A time-indexed density $p_t(\mathbf{x})$

This leads to the Fokker–Planck equation (the matrix chapter).

What this drawing shows

What you see. Shows a probability density $p(x,t)$ spreading and flattening under Fokker–Planck diffusion from $t_0$ to $t_1$.

In the mind map. Chapter 19 — Probability Evolution: Fokker-Planck Preview. See From the book above for definitions, figures, and worked examples.

Also appears in Ch. 21 (Paths vs Densities: Three Levels of Description); Ch. 21 (Determinism of Prob Distributions).

Where to read next

Open Chapter 19 companion →

Read the full definitions, figures, and worked examples in Chapter 19: Stochastic Differential Equations — see the mind-map node Probability Evolution: Fokker-Planck Preview.

This concept is also referenced in Chapter 21 (Paths vs Densities: Three Levels of Description); Chapter 21 (Determinism of Prob Distributions).