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Abstract Diffusion models are probabilistic models that learn a data distribution by gradually denoising a Gaussian random variable. Diffusional models enable sampling realistic images on par with or better than competing generative models, and are therefore uniquely useful for solving image reconstruction problems.
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Diffusion-CAD: Controllable Diffusion Model for Generating Computer-Aided Design Models
IEEE Transactions on Visualization and Computer GraphicsGenerative methods for creating computer-aided design (CAD) models have gained significant attention over the past two years. However, existing methods lack fine-grained control over the generated CAD models, making it difficult to manage details such as model dimensions and the relative structure of components. To address these limitations, this study
Aijia Zhang +5 more
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The biofilm life cycle: expanding the conceptual model of biofilm formation
Nature Reviews Microbiology, 2022Karin Sauer +2 more
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Machine learning methods to model multicellular complexity and tissue specificity
Nature Reviews Materials, 2021Aaron K Wong, Olga G Troyanskaya
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Promoting cancer screening within the patient centered medical home
Ca-A Cancer Journal for Clinicians, 2011Robert A Smith
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Generation of a Broadly Useful Model for COVID-19 Pathogenesis, Vaccination, and Treatment
Cell, 2020Jing Sun, Zhen Zhuang, Jian Zheng
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