arXiv:2606. 03393v1 Announce Type: new Abstract: We propose a novel diffusion model, Flicker-DDPM, which incorporates flicker (1/f) noise inspired by self-organized criticality (SOC), a widely observed phenomenon in natural systems.
By Kexiang Mao
The paper introduces a total‑variance/signal‑to‑noise‑ratio (TV/SNR) framework that allows independent control of TV and SNR in diffusion models. By replacing exponentially exploding TV schedules with constant TV while keeping the SNR schedule, the authors achieve consistent improvements in generation efficiency. The approach generalizes the SNR schedule from optimal transport flow matching and works across various reverse diffusion solvers, reducing the search space to two interpretable parameters for robust sampling in scientific applications such as molecular structure generation.
By Khaled Kahouli, Winfried Ripken, Stefan Gugler, Oliver T. Unke, Klaus-Robert M\"{u}ller, Shinichi Nakajima
arXiv:2502. 10389v2 Announce Type: replace-cross Abstract: Diffusion models (DMs) have become the leading choice for generative tasks across diverse domains.
By Ziming Liu, Yifan Yang, Chengruidong Zhang, Yiqi Zhang, Lili Qiu, Yang You, Yuqing Yang
arXiv:2607. 03517v1 Announce Type: new Abstract: Brownian Bridge Diffusion Models (BBDM) offer an appealing framework for image restoration and inverse problems by constructing a stochastic bridge from the clean signal directly to the degraded observation, rather than to pure noise.
By Ron Levi, Michael Elad
arXiv:2606. 27696v1 Announce Type: cross Abstract: In this paper, we are the first to examine the correlations between class frequency and the multi-scale noise schedule within diffusion models.
By Jiequan Cui, Beier Zhu, Qingshan Xu, Xiaojuan Qi, Bei Yu, Hanwang Zhang
arXiv:2608.29227v1 Announce Type: new
Abstract: In this work we propose a novel non-linear diffusion filtering approach for images based on their channel representation. To derive the diffusion updat...
By Christian Heinemann, Freddie {\AA}str\"om, George Baravdish, Kai Krajsek, Michael Felsberg, Hanno Scharr