Multiple integrals and change of variables

Level UniversityDifficulty ★★★★★Concept⌖ Open in the map

What is it?

Integrals over regions of ℝn\R^n: volumes, masses, probabilities of random vectors. Computed as iterated integrals (Fubini) and transformed with the Jacobian determinant: dx=∣det⁡J∣ du\dd x = |\det J|\,\dd u.

Formulas

∬Rf(x,y) dA=∫ab ⁣ ⁣∫cdf(x,y) dy dx\iint_R f(x,y)\,\dd A = \int_a^b\!\!\int_{c}^{d} f(x,y)\,\dd y\,\dd x
∫F(U)g(x) dx=∫Ug(F(u)) ∣det⁡JF(u)∣ du\int_{F(U)} g(x)\,\dd x = \int_U g\big(F(u)\big)\,\big|\det J_F(u)\big|\,\dd u

Where it shows up in computing

  • Monte Carlo methods★★★★★fundamentalScientific computing and algorithms

    Grid quadrature in dd dimensions needs ndn^d points; Monte Carlo's O(N−1/2)O(N^{-1/2}) error does not depend on dd.

  • The rendering equation★★★★★frequentComputer graphics

    Lighting integrals run over the hemisphere of directions and over areas of light sources.

Where it shows up in AI

  • Generative models★★★★★advancedAI and machine learning

    Likelihoods of continuous generative models are multiple integrals; flows use the change-of-variables formula.

Where is it used?

Computing topics reachable from here, through the chain of ideas that leads to them:

What depends on it

This page has the essentials. A fuller treatment (intuition, formal definition, worked example) is on the way.

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