Web: http://arxiv.org/abs/2205.13699

Sept. 19, 2022, 1:12 a.m. | Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon

cs.LG updates on arXiv.org arxiv.org

Whereas diverse variations of diffusion models exist, expanding the linear
diffusion into a nonlinear diffusion process is investigated only by a few
works. The nonlinearity effect has been hardly understood, but intuitively,
there would be more promising diffusion patterns to optimally train the
generative distribution towards the data distribution. This paper introduces
such a data-adaptive and nonlinear diffusion process for score-based diffusion
models. The proposed Implicit Nonlinear Diffusion Model (INDM) learns the
nonlinear diffusion process by combining a normalizing flow …

arxiv diffusion diffusion models likelihood training

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