cornellius-gp
[Feature Request] HalfNormal Prior
🚀 Feature Request
We would like to use the half normal (ie truncated Normal) available in pytorch at dist.half_normal.HalfNormal as a prior distribution for fully Bayesian GP inference.
One caveat is that it seems like the recipe in torch_priors.py only works on pyro.distributions.HalfNormal...
Motivation
We use a HalfNormal prior in an existing production model and would like to replicate numerics with gpytorch.
Pitch
Describe the solution you'd like
self.register_prior('half_normal_param_prior', HalfNormalPrior(float_value_for_halfnormal_scale), 'half_normal_param')
Are you willing to open a pull request? (We LOVE contributions!!!)
Yes. Actually, @ZitongZhou and I already have some internal workaronds.
Sounds good! We'd happily accept a PR for this. What are the workarounds that are required?
Hi Geoff, I worked with Feynman and opened a PR for this issue to add HalfNormal prior. #2147
