Advanced Loss Function Formulations (v-prediction, L_simple)
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Denoising Diffusion Probabilistic Models, Jonathan Ho, Ajay Jain, and Pieter Abbeel, 2020Advances in Neural Information Processing SystemsDOI: 10.48550/arXiv.2006.11239 - This foundational paper introduces the Denoising Diffusion Probabilistic Model (DDPM) framework and the simplified noise prediction loss ($L_{simple}$) that became standard for training diffusion models.
Elucidating the Design Space of Diffusion-Based Generative Models, Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine, 2022Advances in Neural Information Processing SystemsDOI: 10.48550/arXiv.2206.00364 - This research systematically analyzes various architectural and training design choices for diffusion models, including different loss weightings and prediction targets such as $v$-prediction, offering insights into their impact on performance.