Identifiability and Stability of Generative Drifting with Companion-Elliptic Kernel Families

arXiv stat.ML / 4/28/2026

📰 NewsIdeas & Deep AnalysisModels & Research

Key Points

  • The paper studies identifiability and stability of the drifting field used for distributional matching in the Generative Drifting framework.
  • It introduces “companion-elliptic” kernel families (including the Laplace kernel) defined by a second-order elliptic coupling between a kernel κ and its companion function η, and proves that the drifting field is zero exactly when the two Borel probability measures are equal.
  • The authors show that this companion-elliptic class is precisely the set of Gaussian kernels and Matérn kernels with smoothness parameter ν ≥ 1/2.
  • Using counterexamples, they demonstrate that merely controlling the drifting field norm does not ensure weak convergence, because probability mass can escape to infinity; they also characterize the only failure mode as being restricted to a specific one-dimensional ray determined by the target measure.
  • They show weak convergence can be recovered by enforcing an asymptotic lower bound on the intrinsic overlap scalar (a kernel- and target-dependent linear observable).

Abstract

This paper analyzes identifiability and stability for the drifting field underlying distributional matching in the Generative Drifting framework of Deng et al. First, we introduce the class of companion-elliptic kernels, which includes the Laplace kernel and is characterized by a second-order elliptic coupling between each kernel \kappa in this class and its companion function \eta. For each kernel in this class and each pair of Borel probability measures, we prove that the drifting field vanishes if and only if the two probability measures are equal. We further show that this class consists precisely of Gaussian kernels and Mat\'ern kernels with u \ge 1/2. Second, by constructing counterexamples, we exhibit sequences for which mass escapes to infinity while the field tends to zero; in particular, control of the field norm alone does not guarantee weak convergence. Nevertheless, we prove that the only possible mode of failure is confined to the one-dimensional ray \{c\,p:0\le c\le 1\}. Consequently, weak convergence can be restored by imposing an asymptotic lower bound on the intrinsic overlap scalar, a linear observable defined by the kernel and the target measure.