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  2. Chain rule (probability) - Wikipedia

    en.wikipedia.org/wiki/Chain_rule_(probability)

    Chain rule (probability) In probability theory, the chain rule[1] (also called the general product rule[2][3]) describes how to calculate the probability of the intersection of, not necessarily independent, events or the joint distribution of random variables respectively, using conditional probabilities. This rule allows you to express a joint ...

  3. Chain rule - Wikipedia

    en.wikipedia.org/wiki/Chain_rule

    t. e. In calculus, the chain rule is a formula that expresses the derivative of the composition of two differentiable functions f and g in terms of the derivatives of f and g. More precisely, if is the function such that for every x, then the chain rule is, in Lagrange's notation, or, equivalently, The chain rule may also be expressed in ...

  4. Triple product rule - Wikipedia

    en.wikipedia.org/wiki/Triple_product_rule

    The triple product rule, known variously as the cyclic chain rule, cyclic relation, cyclical rule or Euler's chain rule, is a formula which relates partial derivatives of three interdependent variables. The rule finds application in thermodynamics, where frequently three variables can be related by a function of the form f(x, y, z) = 0, so each ...

  5. Conditional mutual information - Wikipedia

    en.wikipedia.org/wiki/Conditional_mutual_information

    The conditional mutual informations , and are represented by the yellow, cyan, and magenta regions, respectively. In probability theory, particularly information theory, the conditional mutual information[1][2] is, in its most basic form, the expected value of the mutual information of two random variables given the value of a third.

  6. Conditional entropy - Wikipedia

    en.wikipedia.org/wiki/Conditional_entropy

    The violet is the mutual information . In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable given that the value of another random variable is known. Here, information is measured in shannons, nats, or hartleys. The entropy of conditioned on is written as .

  7. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    2.5 Chain rule. 2.6 Dot product rule. 2.7 Cross product rule. 3 Second derivative identities. ... We have the following special cases of the multi-variable chain rule.

  8. Faà di Bruno's formula - Wikipedia

    en.wikipedia.org/wiki/Faà_di_Bruno's_formula

    Calculus. Faà di Bruno's formula is an identity in mathematics generalizing the chain rule to higher derivatives. It is named after Francesco Faà di Bruno (1855, 1857), although he was not the first to state or prove the formula. In 1800, more than 50 years before Faà di Bruno, the French mathematician Louis François Antoine Arbogast had ...

  9. Integration by parts - Wikipedia

    en.wikipedia.org/wiki/Integration_by_parts

    Integration by parts can be extended to functions of several variables by applying a version of the fundamental theorem of calculus to an appropriate product rule. There are several such pairings possible in multivariate calculus, involving a scalar-valued function u and vector-valued function (vector field) V .