SciML / SciML/ModelOrderReduction.jl

Diffusion Map

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Dominant language
Julia
Stars
43
Forks
8
Avg merge
11h 47m
Merged PRs (30d)
14

Description

For non-linear data reduction, Diffusion maps should be considered, as there is good deal of work done here wrt Data Driven MOR methods.

https://www.sciencedirect.com/science/article/pii/S1063520306000546?via%3Dihub

Implementation friendly description at https://mediatum.ub.tum.de/download/1356533/1356533.pdf , page 46

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Research direction

The issue names no files, tests, or entry point; begin by reading the linked implementation-friendly description and the cited diffusion-maps paper. Define the intended API and acceptance criteria for adding diffusion maps to nonlinear data reduction, then identify the appropriate package entry point and tests before implementing it.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
data, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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