Can anyone help me with some resources to learn probabilistic programming with pyro I do not have any background on probabilistic programming I skimmed through the tutorials and examples in pyro.ai but it seems they assume a background in probabilistic programming concepts. Hi there, i’m building a model which is related to the scanvi pyro example for modeling count data while learning discrete clusters for data, and i’m having an issue with the parameter fit where the model seems to have a vanishing gradient for fitting zeros Hi all, i’ve read a few posts on the forum about how to use gpu for mcmc Transfer svi, nuts and mcmc to gpu (cuda), how to move mcmc run on gpu to cpu and training on single gpu, but there are a few questions i still have on how to get the most out of numpyro
There is also this blog post comparing mcmc sampling methods on gpu, and although the model is built in pymc, it uses numpyro. I am writing again about the same issue posted here I have been following this example Neural networks — pyro documentation but either there is a bug or i am not doing something in the right order, hehe 😃 pseudo code of my model For name, value in list(m.named_parameters(recurse=false)) I’m seeking advice on improving runtime performance of the below numpyro model
This function is fit to observed data points, one fit per object I read through tensor shapes in pyro — pyro tutorials 1.8.4 documentation to understand better what’s happening with dim and nested plates There’s an example in the docs here that shows how to construct an exponentiallr scheduler Hi everyone, i am very new to numpyro and hierarchical modeling There is another prior (theta_part) which should be centered around theta_group I am trying to use lognormal as priors for both
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