He shows that we can develop the kl divergence between the approximate posterior. Understanding the evidence lower bound (elbo) ask question asked 3 years, 11 months ago modified 9 months ago In bayesian/variational neural networks one often uses the evidence lower bound (elbo) as the objective function to optimize with respect to the model parameters.
liv 🛸 (itslunarliv) Urlebird
The variational distribution is introduced only to allow a numerically tractable decomposition of (put it differently, cancels out from the right. The marginal log likelihood doesn't depend on : A unified perspective 论文中关于elbo的推导： [图片] [图… 显示全部 关注者 2 被浏览
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以上就是证据下限elbo的求解过程，以及它与vae的关联。下一步介绍在vae的基础上，如何引出扩散模型。 相关阅读 1、 扩散模型相关理论知识（一） 有兴趣可关注笔者公众号： 自然语言处理算法与. 当我们试图最大化关于变分分布 （其中 是 的参数）的 elbo 时，我们正在进行变分推断以找到对后验的最佳近似。 让我们快速回顾一下我们要最大化关于 的 elbo 表达式： 通过优化 ，我们试图使 尽可. Elbo is a quantity used to approximate the log marginal likelihood of observed data, after applying jensen's inequality to the log likelihood leading to the fact that maximizing the elbo.
