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# 🐛 Bug
Currently the log likelihood computed through the use of `gpytorch.mlls.ExactMarginalLogLikelihood` can't be computed correctly with fixed Gaussian noise.
## To reproduce
**Code snip…
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stan 2.19 introduced functions that automatically calculate log likelihood for glms, combining the likelihood step with the previously separate matrix multiplication step. the calculations are even pa…
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The log likelihood functions first calculate the likelihood and then take the log numerically.
The formulas look like the log-likelihood could be written down directly.
- [X] `ctapipe.image.muon…
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Is there a way to use the sgd package for a maximum likelihood estimation that does not fit into one of the statistical families? . I see that there is some placeholder source code for a sgd.function …
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As mentioned in issue #143,
- I actually think that it might be better if `likelihood_contour_data` would not return the `levels` at all. In principle, the levels can always be changed without reco…
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It looks like `stanc` ignores the `-fsoa` flag if any undefined functions are used in the likelihood. Given the following model:
```stan
functions {
real undefined_fun(vector x);
}
data {
in…
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- [ ] replace functions eq 17+ 19 by one function def estimate_maximum_likelihood (maximum likelihood is beta), so [g](https://github.com/EPFL-ENAC/CCFatiguePlatform/blob/develop/CCFatigue_modules/2_S…
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I have a couple of example on my local machine of likelihoods for fitting 1D and 2D Gaussian processes to data. This is a pretty common problem, and it's also one where the posterior can (in rare situ…
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In CI, collect and upload performance metrics for tutorials in machine readable format. The solution must not require changing source code of tutorials.
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Looks like the `lnlike` function in `importance_sampling.py` could be refactored to call out to one of any number (currently two) model's likelihoods. Let's do this refactoring so that we can explore …