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### Required prerequisites
- [X] Search the [issue tracker](https://github.com/NVIDIA/cuda-quantum/issues) to check if your feature has already been mentioned or rejected in other issues.
### Descri…
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Update: I just took a gander at [the source code](https://github.com/RichieHakim/sparse_convolution/blob/7aea68f92c8516cbc148235d4243a898138d4270/sparse_convolution/sparse_convolution.py#L10) and foun…
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The `KernelDensityEstimation` class currently includes the normal distribution approximation bandwidth estimator (see `KernelDensityEstimation::getDefaultBandwith()`) when no bandwidth is passed to th…
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Hi Jonathan：
When I use the distribution generated by kernel density estimation for sampling, it takes a lot of time. And I use the distribution generated by sklearn's KDE for sampling, which is ve…
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I have started a notebook to look at this question. Ramy suggests, look at patients with two test results within 6 hours, and assume that differences in viral load within that span of time is just jit…
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Needed: @KirstensGitHub add text describing how this works, and ideally share code
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I would like to help cleaning up the code related to kernel density estimation, and if possible also improve it. Is this of any interest, @josef-pkt ? If so, some help getting started would be great!
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1. kde = KernelDensity(bandwidth, kernel='gaussian') gives:
TypeError: __init__() takes 1 positional argument but 2 positional arguments (and 1 keyword-only argument) were given
Suggest:
kde …
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part of #7338
beta, gamma, invgauss and recipinvgauss kernels can be obtained through sccipy's distributions, with appropriate parameterization.
Birnbaum-Saunders (fatiguelife) should also be pos…
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Currently the density, cdf, quantiles, etc. produced from a `dist_sample()` are not consistent with each other. That is ok as a design choice, and results in better estimates of each, even if they are…