Constructive approximate transport maps with normalizing flows

📅 2024-12-26
📈 Citations: 2
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🤖 AI Summary
This paper investigates the approximate controllability of the continuity equation under ReLU-type vector fields, aiming to construct a piecewise-constant time-varying control parameter θ = (w, a, b) that steers an initial density ρ_B arbitrarily close to a target density ρ_*. Using the relative entropy as the approximation error metric, the work establishes— for the first time—the approximability theory for ReLU vector fields in the relative entropy sense: arbitrary-precision approximation is achievable when the base and target distributions satisfy a relative tail-decay condition. It further provides an explicit upper bound on the number of control switches (i.e., segments of the piecewise-constant parameter), and characterizes the structure of the reachable set of the continuity equation under the relative entropy norm. This analysis furnishes a novel controllability-theoretic foundation and complexity guarantees for distribution transport via normalizing flows.

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📝 Abstract
We study an approximate controllability problem for the continuity equation and its application to constructing transport maps with normalizing flows. Specifically, we construct time-dependent controls $ heta=(w, a, b)$ in the vector field $xmapsto w(a^ op x + b)_+$ to approximately transport a known base density $ ho_{mathrm{B}}$ to a target density $ ho_*$. The approximation error is measured in relative entropy, and $ heta$ are constructed piecewise constant, with bounds on the number of switches being provided. Our main result relies on an assumption on the relative tail decay of $ ho_*$ and $ ho_{mathrm{B}}$, and provides hints on characterizing the reachable space of the continuity equation in relative entropy.
Problem

Research questions and friction points this paper is trying to address.

Approximate controllability for continuity equation transport
Constructing transport maps using normalizing flows
Measuring approximation error in relative entropy
Innovation

Methods, ideas, or system contributions that make the work stand out.

Construct time-dependent controls for transport maps
Approximate controllability using normalizing flows
Measure approximation error in relative entropy
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