Flow-based generative model: Difference between revisions

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:<math>
e_\mathbf x(\tilde x) = \pi(\mathbf x + \mathbf{T_x\tilde x})\,,
\text{with Jacobian:}\,\mathbf{E_x}=\mathbf{T_x}\,\text{at}\,\tilde\mathbf x=\mathbf0.
</math>
sinceSince the Jacobian is injective (full rank: <math>m</math>), a local (not necessarily unique) [[left inverse]], say <math>r^*_\mathbf x</math> with Jacobian <math>\mathbf R^*_\mathbf x</math>, exists such that <math>r^*_\mathbf x(e_\mathbf x(\tilde x))=\tilde x</math> and <math>\mathbf R^*_\mathbf x\mathbf{T_x}=\mathbf I_m</math>. In practice we do not need the left inverse function itself, but we ''do'' need its Jacobian, for which the above equation does not give a unique solution. We can however enforce a unique solution for the Jacobian by choosing the left inverse as, <math>r_\mathbf x:\R^n\to\R^m</math>:
:<math>
r_\mathbf x(\mathbf z) = r^*_\mathbf x(\pi(\mathbf z))\,,\text{with Jacobian:}\,