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[
{
"name": "GP",
"superclasses": "",
"subclasses": "",
"type": 1,
"responsibilities": [
"has gp id",
"has title, fname, lname",
"has surgery address"
…
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Would be more clear if all parameters were defined at the top of a setup file, as opposed to at several places as the likelihoods are being setup. See comments below.
```
data = pd.read_csv(os.pat…
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Hey everyone,
I have coded up a multi-output multi-lengthscale GP (i.e. separate kernel hyperparameter per input dimension and per output dimension). It is pretty efficient, and scalable combined w…
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Use this issue to discuss [A to Z of NHS health writing in the service manual](https://service-manual.nhs.uk/content/a-to-z-of-nhs-health-writing). Please let us know if you identify any entries we sh…
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Variant 5 in each template LBT13/LBT14 needs to use `trim_levels_to_map` with a metadata map that has the appropriate grade reference ranges. For example, in the "HIGH" direction some parameters like …
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Thanks for tinygp, I find it very instructive and am planning to use it my teaching and research.
One feature I am so far missing is the ability to make predictions on a series of new test inputs a…
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I'm probably doing this wrong...
```python
from OCCT.gp import *
t = gp_Trsf()
import sys
t.DumpJson(sys.stdout)
---------------------------------------------------------------------------
…
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To improve speed of light curve fitting, especially using Gaussian Processes (GPs), we have already discussed adding [tinygp package](https://tinygp.readthedocs.io/en/latest/index.html) to the stage 5…
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Background: I have a state machine with multiple transition rules (the simplest has 2). I want to set up a GP to solve for the rules, however these cannot be evaluated separately, rather have to be …
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The goal of this task will be to create very simple GP based recommender systems. The task consists of the following steps.
(1) Write an example to read the data and create test and train set, for exa…