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This would appear to be a bug/unsupported feature Hi i see that numpyro has an univariate truncatednormal distribution, any suggestions for most efficient way i might be able to implement it (or other single/double. If you like, you can make a feature request on github (please include a code snippet and stack trace)
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I saw that pyro is planning to add at least a truncated normal distribution soon So i set up my code so that for each “treatment” in the “treatment” plate, i draw 5 numbers from a normal. However i want to implement a truncated normal distribution as prior for a sample param
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. I think i am doing the log_prob calculation correctly as the two methods produce the same values for the same data, but when i try and fit the model using mcmc i don’t get. I was curious if pyro would easily enable putting a gaussian mixture model (gmm) as the prior on the latent space of a vae
I took the vae tutorial code and changed the model. Batch processing pyro models so cc @fonnesbeck as i think he’ll be interested in batch processing bayesian models anyway I want to run lots of.
Hi, i’m trying to learn multiple (5) coefficients for each treatment group
