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**Submitting author:** @devarops (Evaristo Rojas Mayoral)
**Repository:** https://github.com/IslasGECI/nerd
**Branch with paper.md** (empty if default branch):
**Version:** v1.0.0
**Editor:** @marcos…
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### Subject of the issue
When using **delta_F_inv_cov="LSDI"** while calling **compute_density_BMTI**, an error appears and the call crashes.
### Your environment
colab notebook, python 3.10…
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**Submitting author:** @rajitachandak (Rajita Chandak)
**Repository:** https://github.com/nppackages/lpcde
**Branch with paper.md** (empty if default branch):
**Version:** v.0.1.4
**Editor:** Pending…
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https://arxiv.org/pdf/2108.00089.pdf
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Hi, this is amazing work. Is that possible to get the log-likelihood of predicted samples using this framework?
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### Describe the workflow you want to enable
Kernel density estimates for bounded data are biased near the boundary because probability mass "spills out of the domain". It would be great to add a bou…
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**Describe the solution you'd like**
Histogram estimation is not present in skpro. Implement them from scratch using the conditional density estimate finding the optimal binwidth(h) and find th…
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Thanks for sharing the good work. Is there any implementation for [kernel density estimation](https://en.wikipedia.org/wiki/Multivariate_kernel_density_estimation) available ([univariate](https://book…
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There are various ways this could be done:
* purely from samples. pros: model agnostic, cons: high variance, need to use a kernel method
* using mixture of gaussians: pros: lower variance, cons: ver…
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**Describe the feature you'd like to have**
As discussed in #277, we should have a long term goal of implementing a density estimation API, just as we have a probabilities API.
The reason is th…