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@fonnesbeck as i think he’ll be interested in batch processing bayesian models anyway I want to run lots of numpyro models in parallel I created a new post because This post uses numpyro instead of pyro i’m doing sampling instead of svi i’m using ray instead of dask that post was 2021 i’m running a simple neal’s funnel.
This would appear to be a bug/unsupported feature If you like, you can make a feature request on github (please include a code snippet and stack trace) However, in the short term your best bet would be to try to do what you want in pyro, which should support this. When i was running the code of the example scanvi, i encountered the following error
I’m seeking advice on improving runtime performance of the below numpyro model I have a dataset of l objects This function is fit to observed data points, one fit per object Hi, i’m working on a model where the likelihood follows a matrix normal distribution, x ~ mn_{n,p} (m, u, v)
M ~ mn u ~ inverse wishart v ~ inverse wishart as a result, i believe the posterior distribution should also follow a matrix normal distribution Is there a way to implement the matrix normal distribution in pyro If i replace the conjugate priors with. So i agree that the issue is with the likelihood
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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