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### Is your feature request related to a problem?
The user should have an easy time to see the visualization of the time series and the decomposition.
The decomposition of the time series should a…
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This feature would add methods to the IamDataFrame to compute Kaya identity factors according to the methodology described in Koomey et al 2019 and 2022.
[KoomeyExploringBlackBox2022FINAL.pdf](http…
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Currently, we only take advantage of savings for computing the kernel gram matrix, and computing a gram solve in GP predictions.
We neglect:
- Efficiency of matrix solves and log-determinants…
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# Adding a Decomposition Class
I am currently in the process of planning some simplification in pyxem and it seems like there is a missing Class for dealing with decomposition/ vectorized data repres…
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How much work would it be to get cholesky working on infinite spd BandedBlockBanded matrices?
I'm wondering whether decomposition methods also allow for interesting weight OPs in higher dimension a…
TSGut updated
2 years ago
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### Checked other resources
- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a…
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The new ivp solvers in `integrate` look wonderful. However, it seems that the bottleneck of implicit methods would be the LU decomposition, that currently uses SPLU provided via scipy. In our experien…
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I am testing PIO performance inside the [ROMS ocean model](https://www.myroms.org). In trying to figure out whether or if I should try using MPI aggregators I found the following in `examples/basic/RE…
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Currently the invertability check is done by calculating determinant. But in https://github.com/sympy/sympy/pull/18647 we came to know that in inverse using LU decomposition we can check invertability…
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For now, linear models are defined using `::PDMat` which not only creates extraneous allocations, but also requires a Cholesky decomp upon object construction.
Since sampling from some linear model…