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Denoising Diffusion Probabilistic Models是非常有趣的,

总结起来就下面一句话They are a class of generative models that work by iteratively adding noise to an input signal (like an image, text, or audio) and then learning to denoise from the noisy signal to generate new samples


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  • 枫下家园 / 望子成龙 / 华裔AI人材真是层出不穷-sora惊艳了世界-而sora 脱胎于openai image generator Dalle-Dalle则是对这篇论文做了工程实现Denoising Diffusion Probabilistic Models by Jonathan Ho,

    Ajay Jain and Pieter Abbeel from Google Brain。

    这应该是 Jonathan Ho博士论文的一部分,Pieter Abbeel是他伯克利的指导老师。

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    • Denoising Diffusion Probabilistic Models是非常有趣的,

      总结起来就下面一句话They are a class of generative models that work by iteratively adding noise to an input signal (like an image, text, or audio) and then learning to denoise from the noisy signal to generate new samples


      :

    • 值得一提的是,Jonathan ho 和chenlin Meng 还合作过一些文章,chenlin Meng 和郭德米(demi guo)去年联合创办了pika 。chenlin Meng 的另一篇文章引用率也非常高Denoising Diffusion Implicit Models。她应该是pika 的技术核心