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the MCLMC example works fast on my setup with a 20,000-dimensional problem. |
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Hi all,
I'm here as one of the types of users "People who just need state-of-the-art samplers that are fast, robust and well tested".
I'm looking to sample a very high-dimensional posterior (image sized) with the use of some sharding (multi-device) and a log-density function that uses a probabilistic estimate of the log-likelihood. This means I need to pass a
jax.random.PRNGKey
to my log-density call in the sampler.Could I get some pointers on the best samplers for this task, and possibly how to throw in additional
args
to my log-density call in the kernel?Thank you!
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