grain - D Language for Deep Learning

[jmh530]

On Friday, 26 April 2019 at 06:35:42 UTC, Shigeki Karita wrote:
> 
>
> I haven't know that GPU support in Stan. That's Cool! Cholesky 
> decomposition always suffers me when I use covariance matrix or 
> something. If you are interested in GPU acceleration in 
> probabilistic programming, see also this paper (Table 2) of 
> Edward (previous name of Tensorflow Probability) 
> https://arxiv.org/pdf/1701.03757.pdf

I think I recall hearing something about Edward. In my 
experience, Bayesian modelling can be quite finicky...you might 
do something to get faster results, but then the results may not 
make sense, particularly as the model becomes more complicated. 
While I often prefer the Bayesian approach, faster doesn't 
necessarily mean better.