arXiv:2611.00800v3 cs.AI

A Discrete-Time Variational Objective for Degenerate Diffusion and Equivalence to Flow Matching

Rares Dolga, Harshad Dahake, David Barber

제출 2026-11-03

원문 초록

Diffusion models and more recently Flow models have widespread application. In this work we consider degenerate Diffusion models in which the per-step generator is deterministic. We construct a modified variational framework and show a formal equivalence between Flow models and Degenerate Diffusion models. For our discrete-time variational objective we show that the optimal degenerate generator recovers the data distribution in the limit of an infinite number of generator steps. Our work therefore provides a unified perspective, showing that discrete-time implementations of flow matching and the discrete-time Degenerate Diffusion model can be considered within the same simple variational framework, removing the need for the continuous-time machinery normally used to justify flow matching models.

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  1. arXiv:2611.00800v3제출 시각 미확인
  2. arXiv:2611.00800v2제출 시각 미확인
  3. arXiv:2611.00800v1제출 시각 미확인

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