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Computer Science > Symbolic Computation

arXiv:2204.01623 (cs)
[Submitted on 4 Apr 2022]

Title:More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability

Authors:Ilia Ilmer, Alexey Ovchinnikov, Gleb Pogudin, Pedro Soto
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Abstract:Structural global parameter identifiability indicates whether one can determine a parameter's value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer algebra frameworks.
Subjects: Symbolic Computation (cs.SC); Machine Learning (cs.LG); Algebraic Geometry (math.AG)
Cite as: arXiv:2204.01623 [cs.SC]
  (or arXiv:2204.01623v1 [cs.SC] for this version)
  https://doi.org/10.48550/arXiv.2204.01623

Submission history

From: Ilia Ilmer [view email]
[v1] Mon, 4 Apr 2022 16:12:48 UTC (201 KB)
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