-
Hello everybody, i am relatively new to Bayesian inference and wanted to try out a hierarchical model. Basically what i want to do is to estimate parameters for individual patients, similar to the doc…
-
Dear SBI team,
Im absolutely loving the package! Very well written and documented.
I need to fit a distribution that has convex polytope support, meaning that all samples `theta` need to satisf…
-
Hello,
I'm new to the field... I have a one dimensional model theta and x are 1D, and I'm trying to use SNLE with maf and mdn.
What I'd like to do is to train the estimator on my data (theta was sa…
-
Hello :wave:,
> TLDR. The [lampe](https://github.com/francois-rozet/lampe) package implements normalizing flows with PyTorch. I believe this is relevant for this collection. I hope you like it!
…
-
Hello,
I am wondering if there may be a way to sample flux vectors (such as would result from FBA) from the results of metabolic-EP sampling. Indeed your method is much faster than other sampling alg…
-
# 🐛 Bug
When training a simple, custom GPyTorch model, sometimes the length-scale of the kernel is incredibly small (smaller than the order of `1e-100`). Then, calculating the Cholesky decompositio…
-
The current version estimates the prior range from the posterior samples, however I have found that this can be too narrow for some purposes. It would be useful if the user could pass the prior range …
-
Dong X, Ji Z, Chu T, et al. Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks.
-
Opening this for myself, will close soon
``` r
m
-
# 🐛 Question
I modified the example at https://gpytorch.readthedocs.io/en/latest/examples/01_Exact_GPs/Simple_GP_Regression.html#Introduction to train and test on higher-dimensional data. While g…