Regression colab example - JAX implementation

[conorhassan]

Hi, great paper!

I implemented the regression colab example (or at least the first VBLLMLP example) in JAX. I wrote the equiv. of the distributions.py by subclassing numpyro.distributions and implemented the Regression and VBLLMLP classes in flax. The model is training but the uncertainty bands are a bit of a mess.

Are there any plans to implement in JAX? Would be keen to maybe help out a little if there was. Would be keen to find the errors in my colab somehow too...

Here is the colab: https://colab.research.google.com/drive/1Rh895u0jP9xEpK7eMOz9JHUX_2CluyLO?usp=sharing

Thanks,
Conor

[JieWu02]

Absolutely it is a wonderful work.

But I have the same problem when performing the classcification task. the UQ is a bit of a mess.
Which parameter do you think is the most important?

Best,

[JieWu02]

Absolutely it is a wonderful work.

But I have the same problem when performing the classcification task. the UQ is a bit of a mess. Which parameter do you think is the most important?

Best,

This is my setting, where 7232 is the num of total samples
self.output = vbll.DiscClassification(64, 2, 1.0 / 7232, parameterization='diagonal', prior_scale= 1.0)