Paper

Two-Parameter Flows for Learning Population Dynamics of Physical Systems

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arXiv:2605. 26285v1 Announce Type: new Abstract: This work addresses the problem of learning the dynamics of high-dimensional probability densities over time using unlabeled samples, without assuming access to trajectory information.

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Authors: Paul Schwerdtner, Tobias Blickhan, Benjamin Peherstorfer
Released: 2026-05-27 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Two-Parameter Flows for Learning Population Dynamics of Physical Systems overlaps with clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", experiment "Add C2 control arm (donor sees marker_B without marker_A) to disambiguate paired-marker binding from marker_B leaking alone". Matching terms: latin, without. Source: arxiv cs.LG (Machine Learning).
arXiv: 2605.26285

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