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Would be useful to visualize /quantify when most classes take place, and when most people are free.
A way to filter the most common classes as well.
Would be useful for planning the best times …
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Hi,
Co-author of [1911.11071](https://arxiv.org/abs/1911.11071) here. Nice work! Glad to see that you are building an openly available API for machine learning prediction of QAOA parameters.
I …
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- [ ] area
- [ ] bar
- [ ] barh
- [ ] colorbar
- [x] colormap
- [ ] contour
- [x] errorbar
- [ ] fill
- [x] fplot
- [x] loglog
- [x] plot
- [x] scatter
- [x] semilogx/y
- [x] spy
- [x] stem
- [ ] stai…
nolta updated
10 years ago
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Bayesian credible intervals can currently be derived using quantiles. Would it be possible to implement an HDI interval as well?
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Another ancient theme with nothing public in statsmodels.
a brief github search with python repos for extreme value
https://github.com/wafo-project/pywafo package by Per A. Brodtkorb but GPL
http…
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I am estimating point density, where I am having point coordinates in degrees, I need a raster(over the extent of these points) which provides a density estimation on each cell.
I have tried on R b…
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Currently WL analysis is done by creating GalaxyWL objects containing GalaxyWLDist and GalaxyRedshift objects. Since shape and position information are grouped in the same object, separated from redsh…
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In Bambi which uses PyMC3, it's possible to plot a smoothed histogram (using kernel density estimation) of the marginal posteriors of each stochastic random variable. For example see https://docs.pymc…
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Hi,
I adapted the example available [here]( https://www.kernel-operations.io/keops/_auto_examples/pytorch/plot_grid_cluster_pytorch.html) to perform clustering using keops.
Here is the code:
…