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I created a deterministic convolutional neural network for classification, and then lifted it to a probabilistic network using pyro.random_module() I took the vae tutorial code and changed the model to. I further tuned the learning rate.

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Are there any examples using standard pytorch dataloaders to train a numpyro svi model in batches I was curious if pyro would easily enable putting a gaussian mixture model (gmm) as the prior on the latent space of a vae In the example below, there are roughly 2.5 svi updates per second which is.

Thank you for your clarification about the shape of the bernoulli probability tensor

So, if i understand correctly, i would have to enumerate through my observation matrix y,. It seems numpyro can model latent integers using funsor, great In this example i want to model 2 latent groups using dirichlet and categorical I am struggling with the ii.

Apologies for the rather long post I am trying to modify the code from the gaussian mixture model tutorial (i have also pulled bits of code from various other posts on. I’m seeking advice on improving runtime performance of the below numpyro model I have a dataset of l objects

For each object, i sample a discrete.

要做一些高斯过程相关的研究，刚接触pyro， 浏览了你的Introduction部分，能在翻译原教程的基础上加入概率图和重点提炼等以帮助理解，着实不错，当然这也是我个人觉得汉.