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Begriffe
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Bijective Transformation

Invertible mathematical function that establishes a one-to-one correspondence between two spaces, essential for preserving the exact density computation property in flows.

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Jacobian Determinant

Determinant of the Jacobian matrix of a transformation, used to apply the change of variables formula in the computation of transformed probability densities.

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Invertible Neural Network

Neural network architecture designed to be perfectly invertible, enabling bidirectional computation of activations and gradients without information loss.

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Density Estimation

Problem consisting of estimating the underlying probability density function from observed samples, solved precisely by normalizing flows.

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Autoregressive Flow

Normalizing flow where the transformation of each dimension conditionally depends on previous dimensions, enabling sequential modeling of dependencies.

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Triangular Matrix

Matrix structure (upper or lower) used in certain flows to guarantee efficient computation of the Jacobian determinant equal to the product of diagonal elements.

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LU Decomposition

Matrix factorization decomposing a matrix into the product of a lower triangular matrix (L) and an upper triangular matrix (U), used to parameterize invertible matrices efficiently.

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Masked Autoregressive Flow (MAF)

Autoregressive flow using masks to impose a directional dependency structure, with sequential sampling but possible parallel evaluation.

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Inverse Autoregressive Flow (IAF)

Variant of MAF reversing the direction of dependency to enable fast parallel sampling at the cost of slower sequential evaluation.

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