Reconciling Approximate ODEs and Noisy Data Using Theory of Functional Connections_v0

Texas Digital Library (University of Texas) 2026 Dataset Open access

Read full text
Authors: Salvatore Calabrese, Daniele Mortari
DOI: 10.18738/t8/n6kkc8
Cited by: 0

Abstract

The dataset includes the code and associated data developed for the manuscript titled "Reconciling Approximate ODEs and Noisy Data Using Theory of Functional Connections". The script includes application of Theory of Functional Connections to (i) an ODE representing the time evolution of soil moisture and data extrapolated from satellite measurements (NASA SMAP L4 data product) and (ii) Michaelis-Menten Kinetics under substrate heterogeneity.

Fields of Study & Subjects

Statistical and numerical algorithms Model Reduction and Neural Networks Control Systems and Identification

Publication details

Journal / source
Texas Digital Library (University of Texas)
Publication date
27 January 2026
Document type
Dataset