[HN Gopher] Interactive Visualization of Gaussian Processes
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       Interactive Visualization of Gaussian Processes
        
       Author : sebg
       Score  : 52 points
       Date   : 2021-05-31 17:54 UTC (2 days ago)
        
 (HTM) web link (www.infinitecuriosity.org)
 (TXT) w3m dump (www.infinitecuriosity.org)
        
       | clircle wrote:
       | This is very nice. Gaussian process regression didn't click for
       | me until I thought of the data as a partially observed sample of
       | size one from a stochastic process.
       | 
       | Practically, I have a hard time using Gaussian process
       | regression. I find regression with splines to be reasonable and
       | fast, and I don't have to fret about the nugget parameter or the
       | covariance function structure. But I admit GP regression has a
       | beautiful theory.
       | 
       | But there is an equivalence between (smoothing) splines and
       | certain types of Gaussian process models. [1]
       | 
       | [1] http://pages.stat.wisc.edu/~wahba/ftp1/oldie/kw70bayes.pdf
        
         | nestorD wrote:
         | For me the good reason to use gaussian regression is the fact
         | that you get an uncertainty on the output.
         | 
         | The big downside is that it takes expert knowledge (to design a
         | proper kernel) and a solid implementation (to avoid the various
         | numerical problems they can produce) to apply them to practical
         | problem. Most implementation either break down very quickly or
         | are not flexible enough for my taste.
         | 
         | I have a Rust implementation [0] which tries to help with the
         | flexibility aspect but it is still _very_ far from perfect.
         | 
         | [0]: https://github.com/nestordemeure/friedrich
        
           | clircle wrote:
           | Yep, uncertainty intervals are definitely easier to get with
           | gp regression.
        
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       (page generated 2021-06-02 23:00 UTC)