4 papers
Verifying global identifiability of parametric linear ODE models is NP-hard
Alexey Ovchinnikov, Pedro Soto
Global parameter identifiability is a property of a parametric ODE model to recover the parameter values uniquely from the input-output data. Not all parametric ODE models have thi…
Universality of Photonic Interlacing Architectures for Learning Discrete Linear Unitaries
Matthew Markowitz, Mohammad-Ali Miri, Alexey Ovchinnikov +1
Recent investigations suggest that the discrete linear unitary group can be represented by interlacing a finite sequence of diagonal phase operations with an intervening uni…
Algorithm to find new identifiable reparametrizations of parametric rational ODE models
Nicolette Meshkat, Alexey Ovchinnikov, Thomas Scanlon
Structural identifiability concerns the question of which unknown parameters of a model can be recovered from (perfect) input-output data. If all of the parameters of a model can b…
Algorithm for globally identifiable reparametrizations of ODEs
Sebastian Falkensteiner, Alexey Ovchinnikov, J. Rafael Sendra
Structural global parameter identifiability indicates whether one can determine a parameter's value in an ODE model from given inputs and outputs. If a given model has parameters f…