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A wishlist for probabilistic regression methods to implement or interface.
This is partly copied from the list I made when designing the R counterpart https://github.com/mlr-org/mlr3proba/issues/32 .…
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Our current implementation relies on Matlab for the gaussian process code (specifically, the GPML library). The whole system is very slow.
Currently, there are several ways this could be improved:
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The currently implemented algorithm in `python/bayesianitc/experiments` does not perform well.
@pgrinaway experimented once with [gaussian processes](http://scikit-learn.org/stable/modules/gaussian_…
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Hello,
I would like to generate Conditional simulation of gaussian processes on a "fine" grid (> 10 000 points). It is currently impossible (memory limitation) on my personal computer, using OT v1.…
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I have a graph that involves several Gaussian processes. One of my latent nodes, a_j, is separated from the next latent node by a deterministic node and a factor. I believe a_j requires a custom messa…
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- https://arxiv.org/pdf/2403.07815.pdf
| **Why (Problem/Need)** | **What (Solution/Tool)** | **How (Method/Approach)** |
|------------------------|--------------------------|----------------------…
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Once #504 and #525 are done this opens the option of extending the distribution interface to allow any parameter to vary over time. An interface for Gaussian processes could e.g. look like
```r…
sbfnk updated
7 months ago
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Currently, the model adds random effects and Gaussian processes silently. The functions should produce warnings when these features are added to the model.
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I couldn't find anything about the technique used by GPy when optimising the length-scales in an RBF kernel with ARD=True.
I'm aware of Log-likelihood optimisation (methods such as conjugate gradie…
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I need a TemperatureTimeseries class for temperature time-series, similar to what I have for the PressureTimeseries class.
This class should include the ability to fit a Lorentz profile using a Gau…