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math.NA2020
Learning Quantities of Interest from Dynamical Systems for Observation-Consistent Inversion
Steven Mattis, Kyle Robert Steffen, Troy Butler +2
Dynamical systems arise in a wide variety of mathematical models from science and engineering. A common challenge is to quantify uncertainties on model inputs (parameters) that cor…
math.NA2020
Error estimation and uncertainty quantification for first time to a threshold value
Jehanzeb H. Chaudhry, Donald Estep, Zachary Stevens +1
Classical a posteriori error analysis for differential equations quantifies the error in a Quantity of Interest (QoI) which is represented as a bounded linear functional of the sol…