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Codes for "Online optimization for dynamic electrical impedance tomography"

Authors: Jauhiainen, Jyrki; Dizon, Neil Kristofer; Valkonen, Tuomo;

Codes for "Online optimization for dynamic electrical impedance tomography"

Abstract

These are the Julia codes for the experiments of the manuscript “Online optimization for dynamic electrical impedance tomography” (arXiv:2412.12944). Prerequisites These codes were written for Julia 1.11. The Julia package prequisites are from December 2024 when our experiments were run, and have not been updated to maintain the same environment we used to do the experiments in the manuscript. You may get Julia from julialang.org. Using Navigate your unix shell to the directory containing this README.md and then run: $ julia --project=. The first time doing this, to ensure all the dependencies are installed, run $ ]instantiate Afterwards in the Julia shell, type: > using PredictPDPSEIT This may take a while as Julia precompiles the code. Then, to generate all the experiments in the manuscript, run: > RunAllExperiments() > PlotAllExperiments() > ComputeStats()

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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