enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Negative log predictive density - Wikipedia

    en.wikipedia.org/wiki/Negative_log_predictive...

    It is used extensively in probabilistic modelling research. Examples include: - Candela, Joaquin Quinonero, et al. "Propagation of uncertainty in bayesian kernel models-application to multiple-step ahead forecasting."

  3. Logarithmic decrement - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_decrement

    The logarithmic decrement can be obtained e.g. as ln(x 1 /x 3).Logarithmic decrement, , is used to find the damping ratio of an underdamped system in the time domain.. The method of logarithmic decrement becomes less and less precise as the damping ratio increases past about 0.5; it does not apply at all for a damping ratio greater than 1.0 because the system is overdamped.

  4. Iterated logarithm - Wikipedia

    en.wikipedia.org/wiki/Iterated_logarithm

    The iterated logarithm is closely related to the generalized logarithm function used in symmetric level-index arithmetic. The additive persistence of a number , the number of times someone must replace the number by the sum of its digits before reaching its digital root , is O ( log ∗ ⁡ n ) {\displaystyle O(\log ^{*}n)} .

  5. Negativity (quantum mechanics) - Wikipedia

    en.wikipedia.org/wiki/Negativity_(quantum_mechanics)

    The logarithmic negativity can be zero even if the state is entangled (if the state is PPT entangled). does not reduce to the entropy of entanglement on pure states like most other entanglement measures. is additive on tensor products: () = + ()

  6. Catastrophic cancellation - Wikipedia

    en.wikipedia.org/wiki/Catastrophic_cancellation

    Given numbers and , the naive attempt to compute the mathematical function by the floating-point arithmetic ⁡ (⁡ ⁡ ()) is subject to catastrophic cancellation when and are close in magnitude, because the subtraction can expose the rounding errors in the squaring.

  7. LogSumExp - Wikipedia

    en.wikipedia.org/wiki/LogSumExp

    The LogSumExp (LSE) (also called RealSoftMax [1] or multivariable softplus) function is a smooth maximum – a smooth approximation to the maximum function, mainly used by machine learning algorithms. [2] It is defined as the logarithm of the sum of the exponentials of the arguments:

  8. Complex logarithm - Wikipedia

    en.wikipedia.org/wiki/Complex_logarithm

    Such complex logarithm functions are analogous to the real logarithm function: >, which is the inverse of the real exponential function and hence satisfies e ln x = x for all positive real numbers x. Complex logarithm functions can be constructed by explicit formulas involving real-valued functions, by integration of 1 / z {\displaystyle 1/z ...

  9. Logarithm - Wikipedia

    en.wikipedia.org/wiki/Logarithm

    The logarithm is denoted "log b x" (pronounced as "the logarithm of x to base b", "the base-b logarithm of x", or most commonly "the log, base b, of x "). An equivalent and more succinct definition is that the function log b is the inverse function to the function x ↦ b x {\displaystyle x\mapsto b^{x}} .