Regarding non conjugate priors

[prantik1998]

I want to know how to perform inference with non conjugate priors using rxinfer

[albertpod]

Hi @prantik1998. Generally, two ways are available:

1. If you are in the realm of exponential family distributions, you can use CVI

f(x) = x
...
x ~ Beta(a, b)
x_ ~ f(x) where {meta = CVI(rng, nr_samples, nr_iterations, optimizer)}
y ~ Normal(0.0, x_)
...

More on it here:

2. Alternatively, you can define your own (efficient) product rule between the distributions you are going to multiply.

[prantik1998]

Thanks @albertpod

I wanted to know whether the CVI method will also work when x is a vector ??

[Nimrais]

Hi @prantik1998, yes it will work. You can check this example https://biaslab.github.io/RxInfer.jl/stable/examples/advanced_examples/Nonlinear%20Sensor%20Fusion/#examples-nonlinear-sensor-fusion.