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Refactor gradient and jacobians as multi-dimensional arrays #20

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Tracked by #25
pat-alt opened this issue Nov 25, 2022 · 2 comments
Closed
Tracked by #25

Refactor gradient and jacobians as multi-dimensional arrays #20

pat-alt opened this issue Nov 25, 2022 · 2 comments
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enhancement New feature or request medium This is expected to be medium. students 🎯 A label indicating that this issue is an expected feature for the student software project.

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pat-alt commented Nov 25, 2022

This is an issue reserved for the TU Delft Student Software Project '23 - LaplaceRedux

I think this is a fairly challenging problem, so do expect to spend some time on this. It may involve some breaking changes to the core architecture of the package, but on the bright side, it should help with some outstanding issues.

Currently gradients and Jacobians are mapped to two-dimensional arrays, since so far I had not considered training LA in batches (see related #19). This currently leads to problems for the implementation of GGN for the multi-class cases (see related #17). Refactoring things properly should help. In this context it may be worth using Tullio.jl for multi-dimensional array computations.

@pat-alt pat-alt added enhancement New feature or request medium This is expected to be medium. labels Nov 25, 2022
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pat-alt commented Nov 25, 2022

Check here for a good reference on Einstein summation.

@pat-alt pat-alt self-assigned this Nov 29, 2022
This was referenced Apr 13, 2023
@pat-alt pat-alt added the students 🎯 A label indicating that this issue is an expected feature for the student software project. label Apr 13, 2023
severinbratus pushed a commit that referenced this issue Jul 5, 2023
Fix Multi-Class Posterior Prediction Issue
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pat-alt commented Jul 6, 2023

closed by #33

@pat-alt pat-alt closed this as completed Jul 6, 2023
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enhancement New feature or request medium This is expected to be medium. students 🎯 A label indicating that this issue is an expected feature for the student software project.
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