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#### Summary:
The number of log prob gradient evaluations per sample is one greater than the reported `n_leapfrog` for that sample.
This does not need to be so; the gradient for the starting point w…
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It says in the paper: "Arguably, this is exactly the kind of posterior summary that we would like to obtain from Markov chain Monte Carlo based or stochastic search BVSR methods, but doing so would re…
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When we run parallel HMC sampling using the vectorised HMC implementation, it is possible to adapt the covariance matrix for momentum variables using all samples from all chains. Furthermore, it is po…
yebai updated
3 years ago
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Introduce Markov Chain Algorithm
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**Is your feature request related to a problem? Please describe.**
Hi I have just got started with jupyter-book and I think it is an excellent project.
I was wondering if it was possible to make…
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Analyze a pair of models together, in such a way that you find the places where their predictions diverge. This is the place to conduct an experiment, as it will give the biggest differentiator betwee…
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According to the book [pbr-book chapter 16.3 multiple important sampling](https://www.pbr-book.org/3ed-2018/Light_Transport_III_Bidirectional_Methods/Bidirectional_Path_Tracing#MultipleImportanceSampl…
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Hi, I wanted to suggest adding a resource to the CRAN task view on mixed models. I've been developing a GLMM model fitting package for R (currently on CRAN as [glmmrBase v0.4.6](https://cran.rstudio.c…
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I have developed what I'm calling the "Reduced Domain Approximation" as a mechanism for overcoming the dense composite matrices that result from effective preconditioning. This should hopefully speed …